{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9341341524806636"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "\n",
    "# sigmoidal function\n",
    "def activation(x):\n",
    "    return 1 / (1 + math.exp(-x))\n",
    "\n",
    "inputs = np.array([1, 2, 3, 4])\n",
    "weights = np.array([0.2, 0.324, 0.1, .001])\n",
    "bias = 1.5\n",
    "\n",
    "a = activation(np.dot(inputs.T, weights) + bias)\n",
    "\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from sklearn import linear_model, datasets, metrics\n",
    "from sklearn.neural_network import BernoulliRBM\n",
    "from sklearn.pipeline import Pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6000, 785)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images = np.genfromtxt('mnist_train.csv', delimiter=',')\n",
    "images.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 255.0)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images_X, images_y = images[:,1:], images[:,0]\n",
    "\n",
    "# values are much larger than 0-1 but scikit-learn RBM version assumes 0-1 scaling\n",
    "np.min(images_X), np.max(images_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(images_X[0].reshape(28, 28), cmap=plt.cm.gray_r)\n",
    "\n",
    "images_y[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# scale images_X to be beteen 0 and 1\n",
    "images_X = images_X / 255.\n",
    "\n",
    "# make pixels binary (either white or black)\n",
    "images_X = (images_X > 0.5).astype(float)\n",
    "\n",
    "np.min(images_X), np.max(images_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(images_X[0].reshape(28, 28), cmap=plt.cm.gray_r)\n",
    "\n",
    "images_y[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7QVa/DJuVyZ9DdHv57Xov99Gt4M8fSf2Z7ajlvhfnmyQEQSB9z0cmk4m1n56z7rU1JAgCKRPL22q1tlz3eR3HaZrt9t7s8QaDwWAwGAw7wJ4xPknsDrVZrfnVajX5DAi1vnw+D6Cj+WUymZiVcre1eF8moCODLluSdeVru/cyowUk13Wr1RJ5q9UqAGB9fR1A2Kb8TV9fHwCgVCrJe9bJXlmeSVayz2DUarWI1c/PfNk2NjYAhHLRzz8wMCD39WXUlue9BM3E8X2pVALQYQaazWasThqNxqZW6V5DzzGEb/lqS7m/vx9AR858Pi/tyfZNskr32ppOkidpvuH7ZrOZ+D0QtqVmuPSrvu/dYrf0+kC0Wi3pd1p+lptjjOtEEjOr14x7cfwBcRa5VqtJPyQoQ6lUknlGMyL32lgkdLvqtvS9A5SvUChE1nveM63+aYyPwWAwGAyGnkFXGZ+kOIlGoyGsDq2rtbU10QKXl5flOiC0ygqFAoAwoBMIffLU8nVcxV5r8q1WK6alr6+vY3V1Vd4DoXz8nq+sj0wmI5Ynd7EMDQ2JrL7Wu1fQ/nC/DIVCQawrHf/BtqPci4uLAMIdEj6LMDAwAO4uowWay+XuilWm/c/sk/V6Xdgdvq6trWFlZQVAh5nU5U1iF3w/NXD3/O9JPnP/s0wmI5YkX3nN6uqqtKmOhUmKrel2+/nP1BZgktWr4644zjiHUPZqtYqFhQUAkDGsv9d1tBdtmBT/oFkdIDqfajaS7UO5BwcHAQATExPgTjJ+1mg0RN61tTUAUcazm7ImsTucIynj+vq6zCn8zDknc6Q/N7LcQIcFKhQKsfZOGrN7DcpTq9WwtLQEINwZCAA3b96UzygTd8gdOnRI5N6sHvYammX02Z1qtSr9NCn2k+DusUwmI3JxzajX6zI/77Zvdl3xSVIMOLnMzc0BiE6orByt+HAC5oQ1MDAgbgUqDcVisetKgk8fNxoNmSg4cSwsLEjH5evs7KzIx+tYH319fRgfHwcAHD9+HADwwAMPYN++fQAgcu7FZKsXQq3kUPFkOwwNDcnkye+q1SquXr0KoKM83Lx5E0C0w+r2pTzs7Fqh7UZAmw/dnr4Lp1qtRgKXgXASZR/kgsL2KZfL8p6KnJ5YddtpF6//XdrQgaysU70YcFLhIlipVOQ9oY0SyjY7OwsgrCe/7jS6scNqs0BJPS6B6ATMflWpVCIuEaDTTy9cuIDp6elIeQcHB2Wx0a4F/dxuwXetaZcPx1O1WpX3WmljW3DxYL+dmJjAQw89BKAz7hqNhtQB5W9vBQaw9UK1W/n8OVUbHL4BCXTacf/+/ZiYCLN3sD15/erqqtyX/VVvpuBro9GIucT2wsWXzWYjCg8Qtt2NGzcAANeuXQMQtgXblkYiZS2Xy1JW1le9Xo+MbT6L6EZf1Ws8769DArTRSFmIUqkUW8c51iqVinzGuTYIAllHue5ubGzsqM3M1WUwGAwGg6FnkBrjk6R1BUEg1oJmea5fvw4AMRYE6FhaOjkb3QvUHguFgrAkZEay2WxEu00bSVsFtXVCbXZjY0M0YFob+/fvF3lIXdItxLIDUSbAt5Cz2WyM1k9bg9eMD8s+NDQk1sb+/fsBAAcOHIjQjwBw8eLFCIMHIBZECnQ0dU19Uo7R0dHEgMu02QJCB0omsS9+cG+xWJS6ICvCa0qlklhb2m1Ga1UHevvP7wZYZ+xbhUJB5CBzMTY2JlYz21azPeyrfA2CQPp7EnOn+2XS1uHdtuNWQemNRkPKxvJqy5+Mx/DwsNQDZaCl/dprr+Hy5csAOpY1WVig0w/K5fKeuPL8cd5sNqXMHEfLy8vCvumAbB18DgC3bt0CAMzMzMg8Q8Ynl8vF2APN5GnXUVqy8dX3CKysrMQ2DuRyOUxOTgIATpw4AQB45JFHZA1ge09NTYmsrDO2WaFQiLlHNAPRzfQMvvs+k8nEmK7V1VVZ51gXpVIJx44dAwC8733vi7yOj4/LPMu2TWLGkubRNAKgdfk10wOEfdOf74IgEHaHY/HYsWMy72h3OhD2Oc5d2k3tQwdI30k/NcbHYDAYDAZDzyA1xkdvNSOazaZYEGQ4ZmdnRUOnhlssFoW5YewILetarSZ+Z76ura2JNugHYrIsRFoafFKQby6XE8uQ5T148GDMv9rX1xeznulTX1tbE3aFmvDY2FgktofPTwrkTEs2vrLsZDKGhoZw+PBhAJDXwcFBkePdd98FAHzta1/DuXPnAHQ0b7Jc+/fvl3gnWgJLS0tiDWi/tJ+6QDNdu8FWCTQ106WDr3VAKBDWhb9lXccQaMscCFnOmZmZyDN1PFFarIEvW9JYDIIgkkoACPss+xw/W1lZkVgtxhqQXchkMjGGc3FxUca2Dtj3x4AOgt8ptgpkrlarwnzQAt7Y2JB2ImMwOjoqTAevY/nn5uZw5cqVSLmBThvrGC4/eVw32TsdD0KWnOPp2rVr8p5l0kw0y6VjsjjGeN+xsbFI2+l76c/01v47xWZsnR/7t7KyImVnex89ehTPPvssAOCxxx4DELLOlOnixTBpPfvtrVu3ZIxxXh4ZGZF29DeYaCSNnd0gk8nEEkYmsaDZbFbG4JEjRwCE3oxTp04BAJ588kkAYfwnENYd59uvf/3rAMKx6LM5ev7UcUxp9Ve9LrFflUolqWuiXC7LuOM6sn//fpljqQvQM3Tt2jWZf1gvExMTsTmsXq/HtvxvJ2VIqsHN/sSk6WdSWMvLy/IZhZicnBQKk9QyJ+T19XW88cYbAKJKAyuZwVBJ9HoajasXYE4AfHY+n5fFnZNipVKRsrPxq9WqNCLdfKRp6/V6LACxr68vQoHyum4F3umB6XcsHdxJl1WtVsPp06cBAH/yJ38CIHQTcPI6evRo5HV4eDim+KyursaCYjVt6pctLRmBeMBtJpOJ7CwDwvY5ePAggI5LoFQqRQLtWGb+z37BxbbZbEb6PbB5ttKdyrmV+weIuqS4yPA3mv7ngn/+/HkZb1TO2RfGx8el3+oAdv+6SqUSy2K9WVl3Cn/XyNLSkkyanCf6+vqkDR955BEAwIMPPiiTLeuG46+vr0/uq9uNygb77uDgoMwL3RqTOlib5VxcXBRljXU+MzMTaU8grHN/3uUYKxaLYlxyrB88eFD6LpXcer0ec/+kJauWyy/n6uqqfE9j+OTJk9J+nIveeecdvPjiiwA6Cz+NsKWlJWlTKgoPPfSQGDB6fdhKCUoDSZnQ8/m89B+uG/V6XdqFMh49elQC0Z944gkAHaVobm5OQguIWq0W2227Wc61NOQCoiEmfO3v74/tyCqVStI/+arzLbFM7AfNZlPGMft8q9WS8bzbzS/m6jIYDAaDwdAzSJXx8bMvr66uxnITaBcHNdvJyUnRzE+ePAmgY2XPzMyIu+Ctt94CEGrHtMJo5R04cCC2xXU3SApIIytA5qNSqYgVoal01oOm0EnLko4ltTc0NIQDBw4A6Fg4rVZL6ovX6XwpacG3RLR1Qq28WCzKe2rnr7/+Oj7/+c8DAL70pS8BCKl0BuKxTqidj42NRbYHA2Ed+u6lcrkcsx66EUTKe+v+wrKQGp+cnIR/qvTKykos0yhf8/m8WG86g7VP5euzn5Iye+8GOkCbz+DzNZvGz5xzsfH56quv4sKFCwA6/ffQoUMAQmuTbcvra7WavOd9BwYGuhLcnPR7nWmZdczxeejQITz11FMAIK+HDx+WNmN7sf9ls9nYVnfNtCYFw3cTPuOjtwSTrRkeHhbrWocH+C5r7U5n/2f73rx5M+bq0sHNacnq12OSR6Ber0eYKAB49NFHhUUl0/xnf/ZnwvicP38eACJB3mQmOd8kBanrcd/NjMd+Ggndz1gXBw4ckDajK2hyclLk0G5MIOwLZHz0phL2Ad1m3cw4rkNANLvjM+jLy8vi9WCdj4+Pyzrv56eqVquRrfBAKLtmLoGwTpNOPrgdjPExGAwGg8HQM0h1OzstBGpoc3NzouWR6VhdXRULRScmpH+TrIdOjEftmKjVapGsnrwvtftubGvXZ/zoWA6Wm/E5QGd77DvvvAMAePPNN/Hmm29GvqPG+sQTTwizQAtnfn5emKzNztzpBvQWWs108dnc6vvyyy/jq1/9KoBOwPn4+LiwdbSuKI/ehqgTi7GN9dZwXtut7cLZbDZmITSbzVjir1wuJ2yItrI2S+ZWLpcj1gqv5z04JpLOIkobzWYzUmYgHCc+m7exsSFy0/qv1WoiG9kdxhk888wzsv2Uffutt96SZ2lZOR66kUxUJ4bUCeg47jmHnDp1Cs899xyATp8sFAoyBsmeaNn9wPNyuSzzlR/f1Q3ocZeUcJJsFst04MABqWuOo/X1dYkBIpOiEzjSymYdzszMiGyaNUxzM4UOGtbMGT/TG0HIgDOu5fDhwzIf/uVf/iUA4Fvf+pYwPH7sZTabjSTk5DWUJ2lzQdobR5I2peizxXRqBJad6yHXg2w2K54NxrlwPN+6dUvGoE4Um8QukTHs9hqi5xfKx/Xh3LlzIoOOMfPTl2g2nOXWjKcfu5QUQ7Ud7Frx0YuIP9nOzc3JJKN3HnDwcgAODQ0Jpad3ZxH60DYgrBwKqTM4djuLqj8odDAwB9ONGzfwzW9+E0A4OIFQ8bl06RKAzkR03333AQgHJt+zDvQCy8m51Wp1PSO1DrLVAYCcdDjQXnvttVgnfvTRR/Hwww8D6AQ1s7yzs7NCx+qM1RzgOnh4J514O9B15+cO0Yoyv1tbW4strklHlOgdMr4CsLy8LIsqlaFGo5G6bEnBp/o4GJbF32mld7pQSW02mzI+uQBRefie7/keeQaDoWu1mrhjWcfr6+tdnWST8r80Gg1Z5LhR4rnnnhP3K+VcWVmROcmfm2ZmZmK7RQ8ePCgKIOsvaXdTN/qr7+7t7++PZKoHwjFD9wavu3nzpowpysHylsvlWC4gPe5Zr9lsNtZfdqsU+O40LSOfNTIyggcffBAA5BWAGI5vv/02gLDN/Gy/DPwFogfPAtFAaj87fBqy+dBudL8dtdGnd0Lpo1OA6Jj189u9++67squLc0ylUpExoAOI00TSblHKoA9i5pygd/1yrHKHWqvVkj5IhYZz7ezsrKw7+ln+Yaa6fi2Pj8FgMBgMBkMCUnV10ZKgxTs9PS1UF7XYiYkJ0UrJFkxMTAg9TQuFmuDMzEyMml5bW4tpwvocmzSx1QGB2mJgeS9cuCABeGfOnAEQar3cxk7ZaaU8/PDDEsymg2J1UDO/S5vx2coa0Nq7ny9jbm5O2CntDvG3i+pcIwxQpzyDg4PS/mzzbm19BpLPytKshA5mBUJmwD8cN5fLSbv4Fn69XhfLSwfe837aemYdpBXAncSS8Rk66zktZJ31XKeD4Hdkf8hEvvDCCwDCjQdk/fTBmH6/rNfr8n0Sg7tT6LHo50wCOu7m+++/H0DIANDy1wc/kn0la8k5qlgsCmtAtktvf9dB8UlzQJrQ2X3JUPT19cXaUDMFZJMLhYLUBediHQTOfsI5WbtD+Ey95Tqtecd3+WSzWZGNDNbo6KgE0/P6a9eu4ezZswA6/XlkZETahYwX23p9fT3GMK+ursayOTcajT052NPPot7X1xdj5HRWbs4ja2trIpt/btkbb7wh/Zfz09jYmNQJZUzbE+K7BHUONH1wuL8h6eLFi9InyRBplzX7J8fi2bNnZd3nmrmxsRE7HFqX6U5gjI/BYDAYDIaewa4ZH60B+udyzczMiMVBi3doaEi2ftNqed/73iefUXulxnjlypXIOTNAaKnwfknWexpIOv3Z337snItsUwaSTzXe2NgQa4TWNP2cjzzyiHynzzDzE2tpDbdb2WI1y6JP5GZ76jgtMnS0zgqFglgqvJ7/r6ysxM4HKhaLsSzNfX19sdOSuyGbf4q3Zgr1WVrsY7Sy9WnftJb19l9amXpbLS0vvdXTtwB3Ax00qi0fWlC0FFutlsjBAOUTJ05IO9Jam5iYkNQSZD+YLRfotCnvXywW5be6Xv3kd2nGwCTFWuVyOelb+vw+zh1kK6empmTDBduJOHbsmPyWcWpjY2PyDD2uu5VaIukzjpNKpSJtpxkfvy+Ojo5GgtqBKEvtbzXWc5tOeOnHiROXLh0AACAASURBVKTFTOr4DM73fNbY2JiwIJxHLl68KEyPThtCxpgsB4N833zzTdlMw7KPj4/Hsojr8detrPj6nmxHzfhsFTc2ODgo84ZOGAoAly5dkjbT/Z7siD8+0oZeA3VCXz6T445zYq1Wi519qDdEcZ4iG3v+/HlhztlOS0tLogOQqd4pY5eqq4uFZ4FXVlZEMNJcExMT0nmpBBw9elQ6rw6IBcLFlu/1YaY+bdntQwP1M/0cP0Cnc1cqFQmo1FQyG480/Ac+8AEA4UCmXBysMzMzkVwr/rO6Be0u5IRZrVYjhz4C0Z0uOjs1F0U/hXhfX5+0vw5O8zN57kVejSTlrlarSR/jIr6+vh5bvBcXF2MuOz3RsL05Sa+vr8tg17mQ/F2Ku4XfN4IgiC18elMBXVjHjx8XxVXnUuLi5284mJmZiU2kOmeHDhbvdn/1d6roYFyWQ7tYX331VQAhlc524sJK+Q4fPhzLy1Uul8UgYV12Y2eer1zoZ+jM7n6OLJ3lXe+O9AO39UHAVBj42fLysvRZfpa0+zEtxUcbcxxv+ggYfx2Zm5uTcUaF9MEHH5QFn9dTKbhw4YIE/mr3u96xmYY8W0Erd/7irN2TOhu+P+4KhYJ8RgWCLr9arRbpt/wdxyLrJO0jOAjdhr7is7a2JuVmnzx58qQcsMqxpTOg68OreV/OSeyTS0tL0if8/FR3CnN1GQwGg8Fg6Bmkxvhoi5eWVLVajWm2Q0NDErBF7b1Sqch1/mFlq6urog3ytdVqxQJDc7lcJCBXf5cGNBWpaWF/W/Pk5KSwAbx+bGxMrDa6uJhJNpvNCg1PbX5ubi7G+Og8FGkjKSWBrn/fdeWci+VsWllZkbZj2TUVTc1c142/pVMHkHeLetaBsbRKZmdnhfGh/ENDQ5EzYigjZaOVxXbNZrORHCiE7yZxzsUO7NzNWV2byUiLj+XNZrOxA1YrlYpYZDrDNNuR1jhZE7Y/78drfFarUCjE3HhpyqjZkCQXpg5aZjD266+/LtfwOvY7uo90FnUd9J3UXt0+Nw/oMBMcOzo/Cl8HBwcj7lkgnD/05hCgw0weOnRI2CJaz/rcPM7hQPqZxQk9p/ksTLPZFJZKp2LgmkE37NGjR2XsTU1NRWTV7kydX83PVZR0HllaSMpVxPWpVqvFckhVq1X5jT6Ak0wPc6jRK1CtVoXN0gexatcvEM1z0y0kMWicV5jiZGBgIJbupL+/X+ZF1ge9JZVKJdL+QHTTj873s5O2M8bHYDAYDAZDzyC1BIbNZjOSTJCv1HKpnZfLZbGm9FZXWoi0QnQSJ/+E4VarFcu0q63MtJkewg/Emp2djWnpjUZDLDBaamNjY2JlPfPMMwA6Vub09LRYLNTmWQf6HrlcLnbGVFrQW7l1QjggjBHwY3d0JmZ+tr6+LsyQHxSczWal/XWMiJ+SQH/Xzey4PuOzvLws2yi3SqOgrSxmqWa76/vpDM5sP22h6BPdgfSzG+tgVX1ytz8+NjY2RG7KevnyZYmVYHAz+0Imk4md36Rjhyh/oVCIxTGlMSa32s6ey+Wk7Vj+5eVl2U5Li7lUKomFqs/GA8K5iXEjZEgWFxe3zHzbrWSUOnaC7aZj0ThWpqenpXxkSt555x1JqcH4pFOnTgEILXGyIJrV5RjXCUb3gmH2tzO3Wi2RkWtAsViUcaTjklh+JjUkY37lypXYmU7Dw8Ox+XMvzlzTTCdlXFxcFNn0mV2+jIuLi7ImkLHUMS6ce9hX8/l84vlqfgLKNE9nz+VysRMNisWirPFkfo4dOyYxPjoImv2Tn9ET0tfXJ0lSGZ+n19ukTU134iUwxsdgMBgMBkPPILUYn0ajEds6CcT9fwMDA6IF6tgOfQYJ0ElkdOvWrZgFoBN5kTXSkfLdgD6SQCdSpA+WsqysrIjFyetGRkYkJoTWFmW5evWq7ECgzLVaTViVpN0B3bIyG41GLLp+fn5e2lUn3qPmze90O9HnzDZaW1uLbd/Uljfvq7cJdzPGh9D1yLrVif98f3KpVBLGR28nBkKWgXWhd3X5cQXaytQxFLtp06Q08v6W+Xw+HzmOAwhjQWhV0bJ8++23I7uXgGg8CS1O/Ux9UjIQjdlLE9ra83dY6u/Zd+fm5uS9nodoIXMe4i6Tw4cPy2fsB0tLS7Edcn19fanveCJ0/It/HM7c3Jy0k053wXZlXMvZs2eFReYY1MkQKQcZIj3G9RZ6nyFIu02DIJA5kvJUq1X5TG875/ecY/SxPjwWgczPysqKMA6M2ZqYmIixS9VqNca+pj23NhoNeZ6Oo/IZ0b6+PomJ5Hfr6+ty8jzbnRgZGREWXTPmfjoQHcfUDWQyGRn/fE3qJ8PDw7GkqhcuXMCFCxcAdBh0ns82PDws57KxXfP5fCyVy04Zn10rPv55Rn5h/CPr9cFkLGCtVpMJlZQ0lYGzZ89GDmEDQoqaCgQ7S7cUnySlgNSyDrKmTIuLi1IXnLgOHjwoky1lYCDe2bNnRWadV8SfgHWQXLco6Gq1Ggsk39jYiAVrcyADncyw169fF7qc13NBATr9gO1VKBQiWZKBZBdNN+AHjeqDGyn36uqqtDPbcWRkRFyWbB8urDMzMzE3LRDP8u2cS90l699H50dh3QJR9yUQLpR0F3DxOHfunBgT7I9cPPQ41UaIDvAGwrrx3ZhAemc9aQXZzxrL74Gwn7Js+gwjtiEPLuXroUOH5Lc0aK5fvy7v9fjrppEFhJO8XgCBsC1pHOkycTzSXXnu3DmZMykb20FvCeY18/PzsUzbSduw04JWQJJyo+nUCkDYZn5utHw+L2OVAeyci0ZHR2NtWywWRUaOiXq9LuOzG+5m/eoj6Qwuv0/Nzc1Je2vZeL2fRsI5FzG6gO4F4rPcSS7RJJlXVlZkfeB6d/r0aWnr559/HkB45iMQTV2j5ePczbbM5XI7UuzM1WUwGAwGg6FnsGPGx6d6G42GWJRJSfd43fr6eizR2+XLl8XFxUCmb3zjGwDCrJ28nlb2xMSEMAe01PP5fFeYEM1Ksby0mGhxAFHmi9Yng0OHh4fFeiNlSQrzzJkzYqlpKt3XYru5hVazLP6p3tVqNdLGQFgX/J7BabRMgHjiu4mJCbGyGVC6sbEhbIOmZ7vJ9ADRRHfa/aEDD/lKS0NnPKZstBR1JmOfZi4UCrFspUlnIKXN/BSLxdiZd/l8XvqXZhbJPJJynp+fj2wtBjr9Up/pRFnz+bzUD+t1s8DY3cqp6W3fDafd5fo8H5aNdT05OYmHHnoIQGerLdu00WiIi4gZZG/cuBEJsu02dHZhndgTCNvBZ0m1Jc0ynzt3LvFMJSAMaGZ7cuxWq1Xpp+w33dgsstU8wrbVHgG23cbGRoRl5r3IWPlnVu3fvx+PP/44gM72aOdcZCMG0N35RocC+H01n8/Le9b34OCglJ/9d3FxUdrZTwtTqVRimbUXFhakr2r3WprJYPkszU75bifdX/jZjRs3ZK557bXXAITt9uyzzwLoMHOU79y5c+KGZ3vp8+v0piq/bNuBMT4Gg8FgMBh6BqkFN2cyGdFek5K60Ud58+ZNsapoqQRBINrdyy+/DKAT47O+vh5LeHjs2DFJtc9ndpvxaTabkfOrgNBa9rfwFwqFGCtQq9UkSSHjK+jnvHjxYiywsFAoRKxnoDs+d19D1vWXlICL8mxsbEiMgT4/jVv0uW2RgWpPPvmkBHcT169fjyTN0/fvBjTLwjpl3EelUokFNwMdtoRlf9/73ifxLrTYaGGVSiVpM20104LRJxcnHTGRRt/VMpIRTdo6TNZxbm5O2pHjs6+vT5gNjmPeY21tLRK/xGf6rEoul0vVkk7qp/7RJjqIVDPOlIV985FHHsH73/9+AJ12ZZufOXNGxikZsLW1tRhD2I0jOXyWXG/g0DGRjH0gEzA/Py9sq2ZwyKxSRtbD2tqasJq8rz4TSiejTPu4HL8dW61WLMFnX1+f9GO2Sy6Xk36nmXDWAVl/xoccPnxYjmXR49RPi5J24lANzW75bFU+n48cIcLPKC+ZrMuXL0uZOX9wLRwcHBQvgmZ5/GDxbp0pp+XTjLB+BTpz6PT0tDA9b775JoAw3pNrOuuBAfqvv/66jEHeX8fx6hiqnWyE2bHi43eYQqEgEz4n3cXFxViwrM6xwIar1WoyAZO21NQ0g2Sp7Bw4cECCm7eKJE8T+rwtYmVlRRpK7+5iObUCSGWPjaizW1MGTTfzt3s52ebzeSmDztJL6F0mOpAVCCebp59+GgDwwgsvAOgErJ04cUI6Jd16KysrMdfEXri6MplMZJcSEPYh/9DV5eVlkZH978CBAzEXEu+ld0/wuyAIIll3gbAdfQU27XbNZDKyGOjy6QBXvvpunH379om8/IwLZbPZjC0eSflmeG3a0Due9G5HIOqK5rOLxaLIQrfzQw89JG3M/kwj5K233hIXtD7riNdRziTlNS3oAG4+gwr68PCwzK38LJPJiNxs18HBQVn4T5w4Ebley8H+Xy6XpZ9oBb1bcyrbTLudtQJLeTgH6VwxvH5wcFDGIt3oev1hPfJe1Wo1kgcO6G5WY+3G9neTra6uymd0O2ezWVF8SALoMxtpTOtDntk+uu78cdetHV06BITznTZ8KAvX83PnzkkYC69/5JFH5OxKzkPcwXX69GlZI/VBz+y7Sbs57wTm6jIYDAaDwdAz2LWri5pXsVgUGo4WVSaTEctJB69pixgItUZqqmRyaIHrTM/8TlOz3WZ69HZZfUoyED2tm5aDzvejtXk/yJXlHh0dFUpbM0R+4Gu3tpbqe2sZaVloi4VlKZVK0j5kBU6ePCmMj+9K0BmC+bqwsJBIPe9FALfPdPX394sr5MEHHwQQtoUfQN/X1yfsh39idz6fj+VdyWazMTZEnymXNnQWY5+Razabwqzp+mbfY36isbEx+czP1VSr1aTNdDZnotupCHQ/TXK/8j0tRc1G0X0wMzMjfZYMCd3q2u2ss9D6eYq60X6+PNVqVRgPnU6Brlbt/uJvOS/pLfscg3qbunan8ZlJ5xx2g4kEOmOBcw2ASF4bP0VBsVgUxkpvZqFMeu4FQkaBIQWsQ32mk88WdgN6owGR5HbW+dI4tth/m82mzEH6RHMgrDs/431SWEK3oHM8kZXSugBl0Xne+Bv2zVOnTgmDR5aLaTUWFhZkrWTb6y38lF27uu4ExvgYDAaDwWDoGaTG+OTzebE49LbCJCuTWi6/c87Jb3xmRJ/gSwsgiRHplq9Wn0lCC0Nnw/WTvQVBIBoqrTOdrVon5eJ9/SyejUZD6qvbmjvQkVGfqUX09fXFtPdSqSQ+Z8YSPPnkk3JyMpk/smG3bt2S2B4yJQsLC7Gt0d2O7wFCC0FvjwTCNqDcmrUkq8X2mZ+fl5gBykMGaGNjI5Idl/fVcSH6mUD3MnDX6/UYs6gzN/OzQqEgfZXtqeM9/KD79fX1WBzN7baTpiGjz3rqpGU6iZsfhAx04irI7ly6dEn6Jb9jHEKj0YgxyXrrcVISyrShg0Y1W8HPOI+wj+lkfZx/k2LLdJwEoZm8vRyDes3QsUdAWMea6QFCRpZjkWxksViUMnMMsr5mZ2elvZNi0fTa0e0YH53agXLpc7l0jBPnQx1byPoh88P5SccE6fm7myyWhmZ8WA6d4d/fVu+ci8XbDQ8PxxL68n99jqeOQU1r3KW2q0sHAfJ1aGgoFpTmnIsd/dBqtSK0q4YOeN3suIG9QFKQY6VSkUmHcpbL5diRHLoz+guGVnL0IZ1+B96LA/Wcc1JmTjDahcNJM5PJxBTUpaUlcRkwkJsuTX3QLF/1ZLuX0Cn+tRuWdcs2WFtbE+WG12vXJhU4BrXr/E36OAX/yBb/fbfg5xTSLo6kDMR+YDbQoeE5oVWr1ZjRshcZxX3onXma8ubiyLmmXq/LWKScMzMzsYBafdAw76tl8tuwm4tLkguBfXJpaSl2wO7CwkLM1QAg0cUKJG8g0Lvk9iJzetJCrRVNlp2L38DAQCxv1uzsrIxfKjlUyvXcspWSsxf9VRvuSdAHiLKv6mOY9KYIXgeE41QfSwEkn5jQLcM5KVePnkP8TTw6PILG8sTEhPRjvw8PDg5GDucl/NxSO+2n5uoyGAwGg8HQM0iN8dHQ7qckrdq3oDSbQW1fa5HaquP1/rP2Ar57LZfLRehYIGR8fKsxCIJYXgVtufkuHx2I51/fbfgBgNlsNpYyQFvBtMAuXLgQcfFo1Ot1kV8zEb6lsFeuLh/ValWYG7bF/Px8zGrSjAdfdbZSfegu4bti96q/+v1mY2Mj1gfX1tbEavaD9JPKrNssiYXtZmCsXzZCM5TsdxyLenzSitZ90++nQDLTuhdMj4+kQFWdEyYpszrrIukwR99tyfv5z9qLMajhz+36kFLKeOPGjRjT1Wq1Nj1gVG9/95/jv78b0P1Iy+MfBruysiJ14TMdmUwmcSzu5VxK+Bm5q9WqsHCUr1gsxjK86zQ2hPZ66PbcDDttS2N8DAaDwWAw9Ay6wvgQQRBEWAziTtmLpBiCu6G1+xq5zjxKy1ln6fQ1cv2Z1syTPttrpmczaG1bB2H7Adn6rCridnLfLSuT0BY1LRNaKjrWRcdl+daN7hNJZ9UkPbPbfXczFiaJzfCzZm8VC+Gc2zLb991gXzVTrLfTsjz61HYglHOz+IDbBU7eLaYgKSaLMXY6eJZjNSnBIuepbDYbm1vu1vjT0HOBP282m83YaedavqSz73y2Use43W3GZ7M5PalcfvynL6t/v73YDHM76E0/evyR8aGcCwsLiR4eIJxfu7n2dUXxSVrQ0myQu91x9UKoqTkgeYAlLUTE3VZsfCRNDlstCHpC8utC416YXH3osvtKW9LuKy1DUrvd7X5JaAVF5yzxKePN+uVmctzOhbWX8usAWWIrSnyrcXY3N01sB9ttQ2KrdtqL7Og7wVbzTdKBmFsp3HfbQN4JtutGTdpNebfhj0W9M0/Pnf48mnT4LNH1DP5dvbvBYDAYDAbDPQR3J5qVc+4WgIvdK07XcCwIgonbXfQelg/49pdxW/IBJuM9DuunbZiM9zRMxja+HeW7I8XHYDAYDAaD4b0Mc3UZDAaDwWDoGZjiYzAYDAaDoWdgio/BYDAYDIaegSk+BoPBYDAYegam+BgMBoPBYOgZmOJjMBgMBoOhZ2CKj8FgMBgMhp7BHR1ZUS6Xg6GhoW6VpWtYXFzE2trabXOX9/f3ByMjI3tRpNRx9erVme0koyqXy8Hw8PBeFClVLCwsbKsNAaBUKgWDg4PdLlLqWFpawvr6+rZk/HYfi+Vy+T3bhtZPOyiVSu/ZfnonY/HbeU4tFotBpVLZiyKliuXlZVSr1UT57kjxGRoawo//+I+nU6pNcLsDHneC3//939/WdSMjI/j5n//5O7r3VmVKOqck6fdpnCfzq7/6q9vKrDk8PIyPf/zju37eXuN3fud3tn3t4OAgPvKRj3SxNHHoNtxpP/3sZz+77WuHhobwsY99bEfPuVNsdqjnTvDpT396W9cNDg52ba5JOvQ4LWx3rgHuTj9NA3faTz/60Y92sTTdwWc+85ltXzs8PIyf/MmfTL0M3T7Q+Hd/93e3dV2lUsEP//AP7+gZPFstk8kknpfnHzbsf74bfO5zn9v0u66ezr4ZkhqTB5z5B57p03r9gyTvBfgHsiY1rl4wKBcPG9SnKxP6ZNr3UmZtXw59WjKRdDr7vQq2Fcucy+Ui/dJ/5XX30gGCGn59J9V/EASbjrNsNiv9NmkM3+vtSehDP4HkE6/1qdj3yqnet4Pui/7CsdUJ3plMJnGs3itIKpNzLtaOvK7RaKBWqwHo1EnSQcv3kqy6TfQc6R/8zDIXCgWUSqXIZ81mM3ay/d2Cvw42m83YAbNaPn9dbLVaiWuq39Y7VZAsxsdgMBgMBkPPoOuMj08rO+di2l2hUEA+nwcQ18xXV1djWq++31bPTBtJ9/Wtp3q9HmOo6vU6+vr6AISyAhB5S6WS1AOv39jYEJnvBeYnqa41hclX3zLW7ADLTxmTWJG7KaPP4ACdslKeVqsVqwvdXymTls23SO4lKxOIl0czV77VXCgUpE23Qrcp+u08X78Cyf2tWCwCiLYhZU5qy6T+vJdyJrGkzWZTyqytYL+d2Jer1ap8xmtyuZzMR3eL+dH1uR3XqnNO+illYj2sra3F5qdCoSBzMNtbt/teyKvlYfn4Wq/XY3OkXgdYVsaElctlDAwMRO6/vr4udbCXzLpf161WKzbvNZvNyDwKhHXOflculyOv9XodCwsLADrtCiCmJyQ9azswxsdgMBgMBkPPoCuMj7a4knyUtLSo2fb394OR/+Pj43IdEGp+q6urAMLdBHzlZ3cDlK/ZbEa0cwBYWVnByspK5LNqtSpMD+XTzA+1WO3T3MpX203rZCvrQMew+KxAo9GQuqAlyZ0O5XJZ5KXVpeNI+F7LnRQrlTZ0O7Kf0nrc2NiQsvC7fD4vFsno6CiADmswNjYmsul+yj6gx8TdYEP0M/m+r69P2kpb+vye/ZJotVpSP+vr6wDC+vL97dlsds8YEd1fdXuybLqcvIY7N312OZvNxuJ9tCzsp41GY1vMVzfA+mS/ajQaUj7NIrOfsi44JxUKBbkHd+rk83kZx5oxSIqLSRNJc42eR/h9vV6PWP3E2toaAGB6ehoAMDU1BSDsm4x/4Rx04MABGbOci8rlstRZN9szKVZFx5ABYf9kG1GuZrMpZT127BgA4H3vex8A4MSJE3Lf2dlZAMCtW7dk7tHMJfvyXjI/PsOqY3bY78bHx3HixAkAnXZiHZw9exY3btwAAFy/fl3KTz2B7avnsDvpr6m1tg6K1MoAJx6/oYEOrTU3NyeCsKHHxsYAAPv374/QX7yenYOVrRWIvZpsgyCI0KtAuIWOShkbv1gsYnJyEgBw+PBhAJ2OnMvlZBJjp11fX4+5uJxzezrZbqVwabkp6+LiYiTwDui0zcbGhrSN7rj8nh1W073dVHz8fqoXyMXFRfmM9c2+mcvlYgGVpJuHhoZERtLRCwsLmJmZAdBZqGq1WtcnIO1OZh/U40Mv7v6ins1mRTk/evQogM6kNDc3h7NnzwIAbt68CSCcdKnwUW4dBN2NPpvkwtKUPifPpaUlKSfrf2xsTCZe9rHl5WUAYR1RBrZrq9WS+7Gva9e1nnS7Pe8450Re7cJhWQ8dOgQgXOTZxleuXAEAnD9/Xsre398PoDP/FotFGc+UVY/Fbsml5dFzhW8s5/N57Nu3DwBkHm02m9JuvAfH2vT0NObm5gAA8/PzAMK2O3jwIABgYmJC7utvpklLVj2P+Qq5Dr6mDO2t15F79Pf34/777wcAvP/97wcAPPXUU/IdZeM99H25HgVBkKjMdwNaUdVGPxDKzu9pLB45ckTWQdb7O++8AwB4+eWX8eqrrwKAKECDg4M4cOAAgI7hOTQ0JPNzkut6M5iry2AwGAwGQ89g1+aY1mypqdMyunnzpljQ1E6dc6K1UzPb2NgQtoOWJzX8xx9/HEeOHAHQodevX7+OW7duAei4TiqVilgy/CyNXABaTj94V1PEfFa5XBZLipro/fffjwcffBBAx9qgpbi0tITLly8D6NCT2s2it1KzrnWQZZrWmLakdYAyZWPblEolqWtq3g899JC8379/v1wHhP2AdCUtAeectBOhXWj+1se00Gq1IgGFQGgd+a7TgYEBYTrIgGSzWWkXthUty2q1KvKwbprNptSBZlRoBfnW5m6xmTsLiLYjZVhaWhJrkWNrbGxMWEm+su+urq7GmIRLly5J27KeBgcHhVVJW0be03evabc66/rmzZsSIMk++fDDD4s8/O6NN96Q/3kdy6vHONmQWq0WY7nSnGu2gr9xYt++fcIK8HVgYEDah24gzjErKytSZu1m8FnapaWlWJB42mxIklxBEAgzyTLdd999ePrppwF0WK16vY633noLQIdFZn994oknRH66gYCoS53w2ZBusLG+y1wHIXM+bLVawliwfJVKRRieZ555BkDHUxAEgYw7Ml2XL1+Wccx79PX1RdhByppWW2pGizItLS3J2CJbs7GxIfMD2ymfz0udkJmlTNPT09J2rKPFxUVZW/X6pDdJsUy3G4/G+BgMBoPBYOgZpOaAbzabopnRipyfnxfNm9r2fffdh/vuuw9AR/ObmpqS2AHtiwdCi4aaIrXIW7duiQVDyzKXy4l1nYbWnpSMzw8EzWQyooHSyq/X62JRnTx5EgDw6KOPCstFrZSW2OrqqpSXTIAO6Nbskh/3o33UO8FmCez0c4EOw0S5KpWKxBWw/icnJ4XNoh+W9fT666+LJUIf7vz8vASZaiYiKag7TWs6ydrr7+8XK5PyHDx4UPodrZLLly9Lf2Yf11u+2cfJGtx///2xgEodA8bP0mJDdNv5MVIbGxux8Xn58mUpv46zYvtxvPH6YrEoTKwek2RfdeyUHzOhE87tFJrloXVMZDIZqVcdZEl25wMf+AAA4LnnnpP7fOtb3xKZgZD5o8waZKs1U6ctaj7LDwbfLXzGpVarSVvorcE+I/v666/jm9/8JgDIvHr16lUAoYz+PFkqleAfuZDL5WTM6npPgynQCff8zzTjw/nhiSeewGOPPQagw+585Stfwblz56RcAIQVqlQqMk7J5k1PT8s8xvuOj48nJtrbzfrhxyi2Wq1YioRqtRoL1i6XyzJm2KdGR0eFZTxz5gyAzvx59epVXLwYJutnPczMzMTiEgcGBmKpCnQQ/06h5fNjVK9evSqB5hxPxWJR1kiWZ319XRgesjt8LRaLOHXqlLwHwvmSzJCeS5LGnWaiknDHik9S3g++6rw1QLios9AMLHvhhRfwfd/3fQA6boLr169HdikAncXzgQceEHpTVyYrQO/+6gZNqTsLK1hTsb5LAejQkY8++iiAcCFk2TgBcWCePXtWFEb8wgAAIABJREFUPiNlqXcZaUWAnToNOTfbDeMPXL2DRe/4YPnY2VdXV0WmCxcuAOgs7JcuXcIrr7wCIJyUgXBiPX78OICO+y8pX5N28aUBPWB0biUqPAzonZyclL7IILu33npL2oiKH+vm7NmzIr+Wi/1YKxh7kWfK33VXrVal7KSfFxcXRUbtEvONCt5LB1TqtuICyUm6UqnE8lClsWBqyl5PhkDUDck2OXr0KJ588kkAnUVxcnJSXCRcRBj422g0ZFHkfa9cuSKTMe+72WKSZrvqjPVUuBYWFqTtdFlY71/5yldEHs6tvI6LiFae2DcWFxdFXr7q3Xq7zVzt14s24PxdZ+xLQCeofnV1FW+++SYA4Bvf+AYA4POf/7z0UxrSH/rQh+R/Kkg01q5fvy6KsR737P/aRZRmO9br9UjgNhDd2cx5ZGBgQMYWjeK5uTnpezSwKcOVK1cirlcgHHd6gwHBPqA3N+w2v4/eFMH+yX5148YNWReI8fFx2ZHGMTY/Py9lZ/2zXo4fPy5z8cMPPyzXfPnLXwbQWUdLpZL8hu2qQyY2g7m6DAaDwWAw9AzumPHx85AkUdnU4kulklD9H/zgBwEAP/qjPyqa/Oc//3kAIeV+7do1AB33F7X4+++/XzQ6asxaU6Q2q3MypEnH6lfen5qlc07KQWu6UqmI/NRiz549K5QeWStqrNPT0yIXtXp9fhe1aO1qSzpbaCfwt1nqfBl87evrE+2Z1uD6+rrIRnZnfX1dyky3Hl0+jUZDmB5Sz3p7Na2zvr6+O87SvV1oGtmvt1KpJGWlezKTyeDll18GAJw+fRpAaMmwPz/xxBOR+y4sLAjjQ0p337598E/fXlpakv6clmvEZ+l09mVatEtLSxFLkjL65/2srq7KhgS+Xrp0CUDY/qSuadH19/eL24v9t1KpxLLk7qYN/d/q7fos/8bGhmzhpSU8PDwcaR8gbEOyj2xf9rmTJ09KEKkO8vUZn/7+fmHD9FzQjUB8oDMHXL9+Xd7rdB9+LrGhoSGZR2lls9/euHFD+jP7g2ZwCb35YLdnzzHTte+qD4Iglhdqeno6tomjv79f2uDP//zPAYTzCMcR5xv215s3b8qz2CePHDkiMmoXbtLYSROZTCaysQEI+wznG523ju3B8jUaDZGRbcA+rs+Q4z327dsXCf3gfZO2ee+2v+p10Q9uLhaL0j9ZnmeffVYYHI7PIAhifYxz8+DgoHhMyORduHBB5iK9WSrJbXc7t6wxPgaDwWAwGHoGXcmIpzODMt7hu77ruwCEmje1NloeL7/8slgyjOdhnMzk5KT4chnEtba2Jr5RWjKDg4OpBhf6lkAmk4lZRRsbG+JzJ+PT398vPkwGFk5PT0s8AT/TWi9loMylUkk0Wh1E6VvRaWUB1tu7aXnRetzY2Igl7bt+/bowODpbKuNZ+FsyRM45kZdMlz5nhhZJuVyOnbuzW/n87dS6HmkVDQ0NReoeCNuJjAD7H9BJIPbCCy8A6FiZp0+fFivnoYceAhCylbTGtM/bD8xNGzpWi31WJ05k/8zn82JB6sBkMrK8nn271WoJW8Q2Hh8fF3m0he4HMqYJnZJAs8CcV/harValT7JfraysSJ9lnyAr8sEPflASxfGac+fOSV+lTAMDA7E+lBZ0f2eb6Iy+fO4DDzwAIIxjYh3z+sOHD8tWdc6/OqaE8ZE6nsbfTNFoNFJPIup7BFqtVizGRmc7Zz+8cOGCMMtkRcrlssjINYNlv3LlingQyDIcOXJE+gD789raWuw8vrQYH50JXc+DQMjMkFnm/PDuu+/GEvwdPXpU2o/fcSMB+yLQiZ8tl8synnUyxKSzydKSL5vNSnk5rwwMDEjfYdv09/dL2Tm3j4+Py9rHPqwzWTP2k/e9fPmyzKM6+a32TmwXOxq1my24/gGUpVJJGpgdcGFhAV/96lcBAF//+tcBhNQ76Uq6uNipnXMS0f72228DCCuOuX24y6RYLMZyMWgabqfQLgPKrPMJcUBSUTlx4oQ0MDvf+fPnRfGhokQ6c2JiQjoH6Wl9QJuOnk8r2JC/9XPmaLAui8ViZIcAZeACyAlzaGhI2pBtzba8fv16zF3W19cXC1AtlUqxAPndIskd6B+SOzY2JhMJXZIvvviiBMGyTKdOnZLAfCo3VI6AThDe888/DyBUZFlPVOyr1WrqWWJ9JLVtNpuN5c+qVqsykbC/3XfffbEcPLzm0qVL0i6cjI4fPy4LM1+3OqR1J/B3N+n7c5GcnZ2VxY4Le6lUkveUIZvNivuR/ZM7v55//nnpk9wxA3QCZHWa/G63IYBYrhfdhtzldOLECXEDsXyTk5PiSuGY5YI4Pz8v7cT5qVgsijwczzrbetqZfpMOU9XhAfyMbVEqlWROYf8rFotirPh53l588UV5Tzf6Aw88EBsTOoA7LQXW7w+5XE5ko9ttfHxc5GGfXlpaku8ZkP/AAw/I4u+3sTZQuFbWajWZb/SOPD9Dfhry6XrTu9CAcD7nmGHfnZqaknVR767TxyABUQKB3/F3U1NTkQBxPovwD0vdCubqMhgMBoPB0DNI9awugprlyMiIWCjUxs6cOYMXX3wRQGdrcxAEor2TwaEWefr0afzVX/0VgA6rMjo6GjtHSAczpb3dm//756vcuHEjlsOkXq/Le9Ky165dE6aHryzrgQMHhLamq+TKlStioVFz7+vriwV07xa+taO3rvN1fHxc2kSzQKx/WlT9/f3iMqAlTeZgeXlZrBlaMAMDA8KyaHmS6n03VnXSdmrNSPL5tILpJpmamhKWgPI89dRTwuqwzLo9GfD8nd/5nQDCuqNrT1vZ+oDaNOBbYdlsNnY2nt7qynbUMrIfj4+PSx2wfLxmZmZGqHkyCUeOHBErU58TxDrW9b7bcamZXD+Dtj7rSKeb4Gc6wzv7KdloWtjDw8PiTucYHxgYiOVX2U5m2N1Cb/Xm68DAgIw77VYmW0e2Uh8wSsaLbXT16lWZW/RBuxwnnG9qtVosQDhtOOdi2ZTX1taErSIDfvToUblOZ1Hn3M/6oUfg9ddfF9n4nd50olOnpJkixJeN5fQzUY+MjMhzyXAAnSBtssn33XdfxB0JdPr7sWPHpA+wfZaWlmS8J2066tbZa5oJBcJxRPneffddAOG6z7HIPlwul6VsDBnQm5z4nu32yiuvRHKK8Zk+k2WZmw0Gg8FgMBgUdkwd+BqyjqehZlssFkVbY4DoV77yFXzta18D0GFwdNZKWpdMWPXuu+9Gkt4BobWjY3uSyrPZZzuFcy6WoXJpaUkseWq79XpdtHhqpxcvXowkJwQ6QYePPPKIxPjw/gsLC7EgrlqtJlZPWpq7rxXr4DCyNRMTE2KJEI888ohYG7Qes9lsLEhbZ2amlU0454TxSQrWTvtcIH3GkZ8OoNVqSfsw+HxhYUH6Fpm4Rx99VO5DK5v9emxsDM8++yyATvzF4uKixEzQcqvX69KPWd9p9VPNeLKv8FkHDx6UIEjKcO3aNRmDZAQuXrwoViMtOZ19lSyJbmP2W1q2Ovg47aR+fPXjNYIgkPLq62khsz6Gh4dl7JFpZbkvXLggsT2sy/3794ulqgP+/bijtGXUSUyJsbExGYs6nQRjJck+jo6OChtCZk5vjGCd8ZqxsTFhhjSTlnbgNqHHHcci5cnlcjJvcF588sknpV70+U1sDzKUjKO8fPly7BTvvr6+yBgEuhuflZR5Xie95HhjCoxarSby8lVvhddbxYGQHeJ45hxz6dIlGc+sV72RIg2PiL/2ZLPZyBZ0IFw7uC7qfkW2X59owDVAb/ahvFz3GUc5NTUl/VP3Z//cvu0gtZ6t99PrHAKksOj2efXVV2XHBCeUgYEBWehJb33pS18CEFKBVCDYCSYmJmI7Y/RkqMuUFoIgkIGmgzlZ2Zx019bWZPLkIJ2fn5e6Ic1Ht8iJEycivwXCTsK68VPjsyxpQnccdl7diSmj3lHCyYMDeHFxUSZZTlxUTvv7+6XOOEjr9XosM7A+nLVb0P2E/XR5eVncBHRN6azjLGc+n5eJhYOSgfcTExMSZEnqeXZ2ViYsPxN3N6AnNj+g8uDBg3j88ccBdBaZq1evSmAv++ChQ4ciuUX09UeOHBG3H2UNgiCykOnf8Xv/s93KB8Trc2BgQBYC9rVMJiNjim29sbEh4/Kll14CgEjeIo5TKhgnT56UyZu/08cNdCsLtwYVlMnJSXnPfvq1r31NMjbTXTk6Oip1wcBXKu/5fF76RFI+Kb2rK01Da7ONJn6Om3K5HMu6rHfRsezz8/OSE4ybZTgm+/r6ZMyyb05PT4uSwTGsjaBuuYF0rhrW9/r6uqxpNPBnZmZkjWR/KxQKMr+yntiOBw8elHFJxe/q1auRNZXy+OMzTeijonQwOscg14Bnn31WFB6ufY8//riMX7YNFdV6vS66AF+np6el/+vDhP0jUCy42WAwGAwGg0Eh1eBmP8io2WyKxkote2ZmRiwMBnE558Qi43WaoqamSiaBz9PX6e3e3cjnow9hpRWZz+dFo9WBgtTmaXX09/eLBk6NlXRmpVIR1yCtGV2PSfls0rZK9Hlj+uwYghaxzr9B1xCtDeectA/pS1rN/f39Yr2RKahWq/IZn79XjA/blO00NzcnLB0tFaBTB2zjjY0Nue4LX/gCgI7FdujQIekDtLpu3rwZ2zpcq9USD2JNEzoTL9tiYmJC2EZt5VJGtvGxY8ekPcggMGh0cHBQ2o9tPTMzk8hm6TwmaUGPRd8lOjw8LLJyDlleXpay0Tp+++235WwusswMaM7lcuKupCtvYmIidhZRJpPpej8FOiED7FdHjhyRzzj+VlZWhFGgK+HJJ5+UrLf3339/5PobN27Egvs1a0fozSLdcgnpZ2iXLBlHssMvvfRSLN/UO++8I4wPGS8yDidOnIic8wWELly6Atme+qzFbrq9tAcECPsR5eEYO3v2rKyVOu8P+zznUubDm5ubk3WR+fAuX74sawjHtXZtpgnNkOl0JCw/24LtcPjwYZk7+N3CwoLIzLbRbjOOXY5n1hXQCXJPOlvNgpsNBoPBYDAYFFKNXvM1r3q9LlYSrYx9+/aJ5UlLenZ2Vvyb1NBpvfX398fOE2q1WpEzS4BQq+7mtr1GoxF5FhBavfRHa3aD5dDbxKl1U06dSZaBeLSis9lsbAut/qxb1kmhUBANnWzMwsKC+FiZrPH69evyGdtr3759kvWWLBXjZjKZjNQJLWkdgEsmLSlJY1qsSNL5QGQ5bt26JfEblGdkZASPPPIIgE6Cu2KxKAwP40PI6AwMDIg8jL949913pZ44DnS22m7FFTSbzVi21v7+/tg2+kqlImNRB7P7Y5DBzUCHOSGDsLq6KhYZf9doNGJxBWlv//blKxQKIhf78OLiopST7buysiJWJj8jc5DL5aR/cuzq05/1WX3s4zrDe5rtqIN8Gc+wb9++WHza+Pi4BNNz+/cLL7wgzBWvYxxMtVqNsORAOF79WLQgCFLPuu3Xj05gqM928plTzdZw/rxy5YrML5w/GcOmGR+dYoH306eVc0xslcx1N9D9nvInJWfVHgV+32q1ZO3z+3Y+n5dg7ldffRVAlMFNCmZPisHbLTKZTIzxqVarMZZ0ZmZG5k7KyU0G/B6I9mvOrUmZp/X428laYYyPwWAwGAyGnsGuGR+9ndRnOnK5nGiv1ECPHz8uvj5qim+88YZor9TayAZNTk6K9khLrV6vRyLzgTCRHrVibd2nqd1SVh27w90TtDoGBwfFz8p6qNfrou2SAWB8wfHjx8WyYzQ/gNi2vWKxGEu2lZZsbLdCoRDZ/cHyMgbiG9/4BoDwCA7WO9vywIED4nf1Y4LK5bJYKqy7hYWF2LlcWqa0GR+i0WgIW8jdhZcvX47EigAhy/P0008D6OyMWVpakpgmbmNnrNbk5KT0D343NTUl7A/bu1QqxRLTpb1tWG8n1/FGTCbG9nn99ddlTJG51CdW08omk9NsNkU2ttnCwoL0W471crnclfbTZ8bx/vqcN72rhNdpZpXlIaPAstGSbDabsRT69Xo9MdV/msfHJN03n88L66rTQrAfcRfMxsaGjEEelfKhD31I5iMyJDp1Avs4n7W6uho5qgII+2Q3j1QhWLf6tHnGKhFzc3OxJIADAwMi96lTpwBAxuvw8HBENt7DZ8uKxaLcTyf8TDsNiv++UqlIWRiDlcvlhFkla6NjyZh6gSz03NycMD2ck4aHh2UMaKYp6dzJnbatf/ah3lWlk/hynmB84NTUlMw17NfNZlNYZc5JnJt1mhcd78t+nCTfnayLu55x9WGI/tZuHbTMRXFsbEwmWR0gS9qSAc/szCdPnpRgRFbAlStXIhmNgbBS/C3uuxm4fufPZDIxl5sOPtO5WfwJ+Pr167LtmTkJuC04l8vFMkLr82o4CPR5OmmD961UKrFsqDolgd7OS5fAM888AyCcdDlBUw5OojpoWiusSfR6t6Bz9/gHpl69elUGIxdFnSuKWFtbk0WeLiIGkd53331Sfg7606dPi/LA77QrtBtbZ/nqB3CfP38+klcKAF577TVpDy42x44dE7l5PdtdK41aoeDiot1O7L/dOB9IjzFtZOkzyIBwHLG8mjYnxc7FlvItLy9L+/N3CwsLUkecc1qtViTQP01QhsHBQSkfZV1dXRVlnQuKPsyRRkWtVpN8VAx8pTtPZ5bXLl8/JEEf5ps2dHuy/XT6DMrN7wqFQuyw3/Pnz4uBye3R3C69vLwsCh/bbnp6WtpKnxHoKwV67OwE/uKrt5PztVwux9xDg4ODseDm1dVVaVPOt7zv6dOn8dprrwHorKOHDx+OGAJAOAezvYk0U0vo8a03HGkXIxCOHcpKZe/RRx8VZY9KHBWhkZERUfa4PszOzkbOIOOz2E/vJJ+PuboMBoPBYDD0DHbM+OhAY/7va4GtVit2cuuhQ4dEg9MZkOkyYoDsBz/4QQChJkyLjNre4uJi5JRePpOaXppWpoYfsFkoFOQzWk+NRiOW6PCll17CX/zFXwDouLP0mU+8jnLW63XRfHVgZdoBov72/1KpFKEhgagLgWUaGBjAU089BaDTTqdOnRLrilo8mYByuSzWjA4s9d0K2Ww2dnZPWjJqxkezhEDY/8hqkfFaXl4WeWiBaUbgO77jOwBA6mFwcFDctcxMPjU1JXWgTzz3t7emhaQAbo6ZfD4vrCpdl2fPnhVrUZ+5xj7AfqFPTvazbQOIuXb7+vq6cpYV2y2fz0eyRAOd8QdEmSoybuyTR44ckSBgwg921u+XlpbkfhynSSkJ0nY7F4vF2Fl2MzMzUi5u7W02m9J3yTQ2Go3IGUn8DIgmA+Rna2trEXYWiM5tacuo1w6Wge2Ty+WEcWQ/LBQKsWzrx48fl/rh2GKdnDt3Tvq4DsznOOZrs9mU5+v0BLtN1AhE3UusW/ajkZERcUUycH1gYEAYEbJV2Ww2limeSRr/6I/+SNqWLqGJiQkZx3pu9V26u4F/r1arJewOx+Da2prMo1zXi8WiyEqvzvj4ON566y0AHV2AY/PEiRNSR2Q5+/v75VlJa/2dtJsxPgaDwWAwGHoGXdnOrq11sgXU9kZHR0V7pTY7OTkp2t13f/d3A+gEzd66dSuyPRgILS/tpwWijEgaFkrSmSS+1dFsNmO+zGq1Ku+5/fuLX/yiBKCxvLRmcrlcZGswn8nvtZVLpG15adACYv2OjIyIz51b9kulkjAejMUaGRkRzZyvOjEh5dDHchC0aJNYnt0GqCf512kV0bqYnZ0VJo7W1tmzZyUOi7FLxWJR/NMsE2OXzp8/L/EU9L3Pzs7G4r30uXTdYnz0fdmec3NzYpFx/G1sbEjds21PnDghMTDsl7zH6uqqsDv8rFKpxPpokmW5m7gJnz1KSlPfbDZjMUxnzpyRzQQs76FDhyJbgikDEFqdOuEdELabnyxVW9FavrRjJ1g+fRI15wW2gz4b8Mtf/jKAaEJOgjEiZCyBaFwL21AzPt3aYMD76WMx2Dedc1J2zhXOOemznFsWFxelXrg+sP3ffvttYX8ow/j4eOSYFT6zW2kziI2NjUiMChCNF2Ws4P79+2OpF2ZnZ4Vl5D24ppw/f17GLFMXHD9+XOpEeyDShD/uarWa9KMktp5l3Ldvn7xnX7x27ZrIzP6sUzPwGbofcP3UjJO/Lm8Huz6kVE/iFFjv5PJzh9Tr9ViA0uTkpFQG6UtSla+88orkTOHi1NfXF8tvoPP4JAUfpwHKog+O07s/gLCjs6Go7Ny8eVPKxIAt7hTq7++P7e7RBz8SerJPC35+h7W1NaEcWZbh4WEpK+uyVCoJHU25X3rpJbz44osAOgd9sm2OHTsWcZMB0U6sB0rauSaSDsvk5E93YyaTkcmTE8e+ffukrNqFwwHKiZhKzq1bt2RSZh0ODAxEDoIEwvbu1uGPRDabFTm0YsC6YNuVSiWhyemye/7556XuOe7YjgMDA9JmVBa0IqcnI0IrYzsdi34b1mq12C4f55wsfKz/ixcvyiJKJbdSqcj41WfpAaFBxQWD9Tc6OhozqHy59Otuwfuurq7KPEkZx8fHZW6hgjY1NSVy6GBX9jEq6gz8PXHihJSVi042m5V+rQNFu3l+lX4FOoubDrTWrju6RLRS5O9O4++Wl5elzRj4PTAwEMuMr9csIi1Z9aHIdEXSpXrr1i15rw8A5vpG9+yNGzciwcEaH/rQh6RttTvJz2+XlEcoTfmAjpJFo3F9fT12btbk5GQsjOLmzZvSFn4/bTabsn7qTTU6P5GPO8kZZq4ug8FgMBgMPYPUTM9cLhfZxw9ENS9Sj7Ozs2JdU6NfW1uL5QKg9n727Fm5jixPpVIR7ZGfpZ13IinLKKFPN+Z7WsDFYlE0WlqNR44cEVceqTyyKIVCQaw3TW379dHNrd6k8BcXFyUAloxTEATC1uitvswjQkvsm9/8Jl555RUAHWuUGY8nJyfFXUTrFYjXcTfOP9K0OhDKRXno0hkfHxeLiu156NAhsaTYny9duiSpFchq6bPlaIVw6+3g4KC41bS7olvb2bVbj8/TVpC/Bfyxxx7Dk08+CQB47rnnRG5anEy9wPv29/dHmB7Ks1XW2zRcCb6rSZ8LyHKUy+VYnq2hoSGh12n5FwoFsUzZ1/V2dn3qs371ZehWjhuOgZWVFWFkiL6+PmHr+HwdVE/Le3R0VMYez3Yio16tVmP31dl3NbolI+tRp7lgH6vVapFAdSCcl8iMcBzn8/mY9c+609n+9VmK/rbnzXI0pQHtstShEUDIWpHxIYM1NjYm35MdnpiYkPJxbaC7bmJiQu5LRml5eVnm7W63nU5jo3N6ASGTyPWerJxe4/l68+ZNWRc4F1PeM2fOiJ7A++pwj6TxeScwxsdgMBgMBkPPYNeMT1IyKr0Nlpqt3tJHi4vfVatV+YxaHrXZer0uGrDOYkyrfaskW2mwJNrPrRNqAaHlTIueDFR/f7+wVQxc04kV+RnvsbGxEclczGf5Vkw3Tw+mpby+vi5WMLVsbdHrjLgMGmUitTNnzghrQiubftsDBw6IJa2tHzIpaQfgJYH1WK1WY1shx8fHhaXh69DQkFhSOqCQ1nVS8CT7KftEX19fzNfdzXbkM/SYYNstLS1JPZO5Gx8flxgfln1tbU2sUMYc6IB3f+u6ZkKTYnvShD5bitBboznvsA0fe+wxmWPI+JTLZWEk+apj68jykTXK5/Mx1lCfDp82dGJElp1xG6VSScYg2/jo0aORrPhAlPEh06y3GnN+0sGo3T5bTUOvGT6bDCAW/L+0tCTy6DMMOd/4iTa190HH6XEe1mxMt7bq6zmGfUnHgXJssexXr16VsUhZDx8+HNvaT6ytrclaybmoWq3GGJntnFS+EyTFZRLNZlOCsnVgMucOxuBRdqBTX/okBt9z1N/fL3IlZXHfk+Bmgg/VwcX6cE4KScVmZWUlUhlAKJB/pAEXj6QMv61WSxQHf9dO2tgqn0+hUIil0N7Y2JABSRlKpVJsIOpIf0522r3kT0BpZ4hNQhAEUoatKNNsNiv1z4k1n8/LxMJFhgqQppkptw62JdIORk+CzquhJyLtYmBZ9CGmQDiIKTcnKf4/NjYWcbvyWX7Abzfl0/f2g39LpZL0S75OT0/LTkkusqurq6L80iWiXQp+oG+SPN1uwyAIYrnAMpmMfMZFfv/+/eIaoAy6HrjY6g0SHJ96fvFdsHvRT3UuJv/YDaAjjzactKuci4p/j8XFxVigbNKxCt1U0LfqO7lcLpa/aHJyUsYW51QgmvkfiB6SqV1iQHR96KZSR2jlSgfKA9HNOXoziV+ufD4vfc/PHr60tBRTjJPWiG658vS6xLHCNby/v1/WBd2P2Cc5vywvL8d+qzdN+XnE0sxCba4ug8FgMBgMPYPUgpu1e0Zru9TaqeGOjIzEKPlisSjf6+2pQJQhoqXearUiTJO+fi+gs2L6VnS1WhWmgJ/pbMF6+yIQavX+WVXawuy2Zamh61UHpWqGi6/UxvmqDxb06Xh9PpBOebAXLJYPzRawv66ursYYLp1jRGcLpcuO1+s68S22veyT/nNZt5SxVCrJe+2SpntA5/bhe9/FqRkfHXSftN272/AzJ9frdWkTflcqlYRe165xP2CU3zUajdgc1mq1YgzFXsqpoZlgvXWf8yPHW7PZFCbBZ6T1WNRunr1geny0Wq0IAwyEfcxnpIBoYCuv1+47IOoR8JmezeTaC3l1Nm4gyphzbtEuMeLSpUuRs+g06vW6yJ/EJneL6fGRyWRiXpeBgQGZJzl3NBoNYSzJ2q2urko5yfjoMBLf1ZXL5RIPXN1RuXf0K4PBYDAYDIb3ILqSSU1r0UnJ2nzLE4gePQ8ksx+8XmdJ3UsLxdc2dVZOXV6WSZ/m7meX5O/q9XpiQNrdsi6Tnusnpmw0GhHrCoimE/A2gVz4AAAgAElEQVSze+rtqVvJs1dtuRWzptvAtyoKhYL8xrdAtTWeFPi31+3ox9vp93rrsD6fCoi2rWaL/Hvotko76eSdQD/b3+igzzoii6ADo/1NBZtlhL7bTA+h5wWiWCwmxjv6Z1CxLZNOH79bzCQQHx869k9/5wewOueknxIck5qFTIpfItLKtr0VkuLB8vm8yKbnEX/bu94AksSqJsWe7cUmis2gn+1vRNDrIuPo9KYf9mEdu+dvKtDz6m7jtLqq+GxW+b5ASb/V13YrS+qdwl8w7yTvjD/AtSvpbk+oGtspi6ZR9cK6WXT9XuQ/2Ql0P0zK25TkuqK8SZNON/IQ7RTa3axfNbTbL4km1xMT73kvtR/+f/a+LDiu6zj7m33DMlgGKxeAFHdxk0WJoixLtqTEsh2Vl7iSiqvsJJWqOOWX5CUvec6L85AnV+yqbJWtyqnYf2I7dmzLlk1tlERRC8UNhEgCJEiAAIhtFsz+P4y/np5zLykAc0FKwvleQGIG956lT5/ur/v0gXv/9NoyDR+ND9K6Wwnc5kgbpXf6m5Xo2nsJvamZsnu7eTKTX4nbbYr3MvQMuF/se6dTZXpvuFNawN0Ka60U2mnUxqlp7LnVjtLXibjNu1enDm2oy8LCwsLCwmLDwLcar8fn800DGHvfL37wsLVarabe70sf4v4BH/0+rqh/gO3jBxxWTn8D28cPNGwff4OPYv9WZfhYWFhYWFhYWHyYYUNdFhYWFhYWFhsG1vCxsLCwsLCw2DCwho+FhYWFhYXFhoE1fCwsLCwsLCw2DKzhY2FhYWFhYbFhYA0fCwsLCwsLiw0Da/hYWFhYWFhYbBis6sqKWCxW5c2qHyYsLCwgl8u9b73yeDxebWtruxtN8hxTU1MzKylGFY/Hq7wJ98OE+fl5ZLPZFdWcb2lpqXZ2dq53kzzHrVu3kE6nV9THeDz+oV2LK5nHRCLxoZ3DTCazojlMJBLVjo6O9W6S55ibm1txHz/qewbw0depiUTiQ9u/28npqgyf9vZ2fPWrX11TI/T9OSvBne4wWS3+5V/+ZUXfa2trw9e+9rWm37fatnvR129+85srqqyZTCbxJ3/yJ2t6h27nndp8u3tnmsHf//3fr/i7nZ2d+Mu//Mum3ncv8M1vfnPF321vb8cf/uEfrl9j1gn//M//vKLvdXZ24i/+4i+aft+d9I7bvYDN4m//9m9X/N2Ojg584xvfWNN7VqtP3+9Zq3nOt771rRV/t729HV/5ylfW0qymwLuc7nTH1Z3w7//+7yv+7lp06krH25xnN7271n1jpTo1mUzi61//+presVasdu90w7e//e3bfrYul5RqrOTyRw3zVmGgfqmZvjn5g3TBHnDnW3P9fr9cJMdL2/gdt1vAg8GgfP9eX8wKOBedvkFZX8DHeXK7IZi39HJ+3S6V/CBgtbfHcxz0Ld764sxmFbCXMPum2+R2iSUvZGV/IpGI/Jt/m8/nb/v8uw03XeN2gSPllGuRfcjn8/IMXqAYCAQc8n+v+6lxO13KvnFe9QXC7Bvnt1QqOeTzg9BH87ZyDX1zOedY30Svbz0H3Neu3++/Z+vSvHxUX0jq5mCal80Gg0GZP31R9AcNbLff73eVKXOf09/nZ5SDfD7v2XzZHB8LCwsLCwuLDYN1MRXdaDhabdFoVCxUWuXlclkYgYWFBQBAJpMBUPNcEomE/C2/bz73brIGbv3TFiv7R88qHA5LO7PZLIBa/BEA0um0WLnhcFieoZmUewntidDaLhaL4l3puWxpaQEAtLa2Aqi3PZfLSX9NpuiDAjdvxKSVA4GA9Mlkt/ScaWaMHpob83M3vE3tMbIt2nvk7zTjw37E43EAjXLMNagZPMqCl+GXtUB7i0Btvthe/gyHwzLueg0CtbVJGdZyzbHh31UqlbvaR/0uc4xDoZDDM/b7/TIny8vLDd+PxWKiT9mfTCYj7Ilen3ezj1qP634AtT6yP2zn8vKy9I06lTIZDofBnBTOp2ZfiXspp6ZM5XI5ab+eC7PNlOOenh7Rs0SpVHIw6/dCTqvVasNaARpZOzcGmX2+U1ShUCjI95tND7GMj4WFhYWFhcWGgaeMj8lSBINBxGIxAHUWoKurCzzJwM+WlpZw4cIFAMClS5cAQP6/vLwMnu7o7+8HUEtC5t/SKgwEAuvucbrl29Dz1ywP+0pvo62tTdo5PT0NoO7NLC8vi5Wu8wrM/Ip75WW6xcF9Pp+MAdvZ2tqK3t7eht9p74NjQlYrnU7L59pD1++4W9AemPa2+G+2JRqNoqenBwDEo+RnHR0d8juO3ezsLGZmZgDUZBzwNk79fn1iP4DaHNBD5s/5+XnkcjkA9bFva2uTfgwMDAAAUqnaYcHOzs6GvgE1eSZL65absF4w+6fnS+d3ULaoL+LxuMwJGZ/x8XEAjQyRniOdC6Pfbf7ba5h91L/T7LCZb5XP5+V7mzdvBlDXna2trcKQ3LhxA0CN8dFyQqw3m67ZDDeWTv+OMss5XlpawnvvvQcAWFxcBFBnfmKxGLZt2wYA2LlzJwCgr69P3sVx0rqXz10PmDJSLpelP3NzcwBq/SHzqFkPyrJmrvgZ28zP4vG4REq4rovFoqcHhdyg28t3sm06j47vZ3tDoVBD3i5Qj/iUSiXpC/vc0tIiukmvcf7tataiZ4aPz+eTxcgNvK2tTYwWKs/e3l7p7JUrVwAAly9fFiGmUqIQ53I56RiFZOvWrWI8cSD8fr88VyeMrQf4nlgsJv/mRMRiMfBIPBVmNpuVftHw4aQuLS2JAubvuru7RVHzZ7ValcXiluznVb/uRAdTKabTaekv56G/v1/mn5siN5RYLCbzRKU2PT0t3+PvWlpaGhKDgdsnbzYD0/AoFouOUGuhUBAZpDynUimZx8nJSQD1eR8eHpY+UslGIhGZK72ITQXktSFUrVYdya3pdFqUIduSzWZlfLVjQgOWbec8LS4uNoSb9U/g7hmrlUrFsWFls1kZR85XNBqVcB03lbfeegtnzpwBUDdGu7q6ANTmsLu7W/4WqPXJPHBRKpUcRoHXuqZarTrGWDs/OpGX7Rsbqx3svH79OgYHBwEA+/btAwAcO3YMQE1e33777YbvVyoVkWOuO22ge20A6VAW30vd0draKjqPenRpaUnmijoQgPSRoTsacpcuXZK23nffffJdbrg3b94EUFvrXO9uIRkvoFMFaHBlMhnZB9ivcrkse6ROFTCdFcrxq6++KvO+fft2AMDu3bsdBlI6nZb3mqFgr/rHtvE9xWJRdI2WU9oCNMZ1mJbf49q9efOmrF3u+9oop44C6nK5mvCeDXVZWFhYWFhYbBg0zfjoJGNab/SWEomEWO+0MkdGRoQJoOc1Nzcn1h2pyccffxxAzYq7evUqgJonA9SsczdmwGR6dMJps/1ze1Yul3NY4uFwWDx+eixjY2MYHR0FUPdQOUaZTEbCemz/4cOHxern9/TntKa96J/uo55DzUK4UeMsSkZWKxqNivd0/vz5huceOHAABw8eBFD3Cubn5zExMQGg7s1EIhFHOHE9GB9Ch+LIghCRSES8f4a3QqGQeItkfjQDZIaN3BLT3Vg1wFvWRzMDZtIgUGdJu7u7he3Qochr164BgMgs153f78eWLVsA1FmSUCgk3rr5U/dLh0fXCh364dwxzJHJZMTjozeoE5O5xr7//e/Lv8kYfOITnwBQYy2Hh4cbnpFOpxv0DtB4uMJkYLyCLnOhw7DmGJZKJZFJ6smLFy82MH1ArbAif544cQIA8MorrwAANm3aJKEwfeDEDP9Uq1VP16PP55P3Uf5SqZRrOIMMCds0ODgoTAfH6cUXXwRQ0yemrozH49JH6tTr16/LOFGe2M9moeWC/9YhZv6bbNXevXvx4IMPAoDo1oWFBZlTgrJ448YNnDt3DkBdPw8MDMj6ZL8rlUoDY8i2ecXeaUZLM8rU83pfJ/tI/VAoFKRN1KO0F/r7+0V2ucavXbsm40Z56ezsdPRvJbrUMj4WFhYWFhYWGwae5fiEQiHxBmg9z8/Pi6WuPa/Tp08DAKampgAAe/bswSOPPAIAeOqppwDU45YLCwv41a9+BQB444035He0+LQHYsZpvfBOdGIYrVg+f2lpSVgLMgb9/f0Sw6QFfPXqVYlTkkUgAzI1NSWeNWPuXV1deOCBB+R5fBa9HY5vs16mW7I2WQpa5UtLS9J2Jp5XKhXxmshq3bhxA++++y6AulfC/J8nn3xSrH0+//r16/I87T2bc+Z2pHOluB2zQpZKF0ijp8EY89DQkMTciZmZGWEJ6ImRPchkMsKUkPGLRqPitVA+/H6/jK0+Cu8l46OT49mfrq4umSuund7eXvGquRZv3LghcqaPefP/Zr5LLBZrYH+A2lrXuWn83VqgvVOdw8c1QA9waWlJvGeusV27dkn+HNnlyclJ7NixAwDw27/92wAgnnYqlZKE7v379wOozRvXMb3ScrnsKK7XLBtiMkiaLdSlQMzCfPl8XsaWczg/P+/Iz6IePn36NP71X/8VAPDmm28CAI4ePYpnn30WQF12FxYWxNM227FWmH+vk+DdDjiQpXr33XeFbeY6eeSRR0RHcm3xOxMTE9J2jsPi4qKsZ+queDzuKHegj5WvBW5FLvk8nQPDtuzatQtAbd8jW3Px4kXpB9vF/ZBJ24uLi8Kw82cgEBC2jKxRsVhseK8ek2ag85b4fp2rSqaHa+3IkSOii7gWR0dHG9h+/dz+/n5Zg9RDp06dkr2IOqyjo0PWhG7T++nTpg0fCmyxWGyoCwHUlBKVBhfe6Oio/JsKavv27RLionLmYI6MjMhA0TBIJpMOZahPMhBeJluWy2URGG4E09PT0hdu8o899hg+/vGPA6gnwGazWdkwP/axjwEADh06BKCW4H327FkAtSRvoCYEZqKbGz3ZLGVpKp1QKOSo6ppOpyUBj+8aHh7Go48+CqCuKC9cuCAbD5PYuKh37Nghc83x8vl80kdtFJgnELyi1vm8cDjsqEEUDodF7jZt2iRt5/doyAH1eWbb+Xejo6PSR2762WxWEvipiH0+n4yZVpI6OX+t0CE2KgMqzlQq1XA6i22h8cl1mkgksHXrVgB12eP86A1Vbx7mac5YLOaot7FWw+d21WvNqsvlclnm5qGHHgJQo9dfffVVAPW5fuaZZ/CZz3wGQD2czvk9efKkGA+U5XK5LDJLw6dUKkkSKdFMvS0977p6u9uJUW4oOoTJOWHIq6OjQ+aOOpk6q1QqiTFEtLa2SojP7V4tfaiimTCQuRmVSiUZN+qYarUqziQNgHPnzol8cjNcWFhwyC4dj2g0KmuQRvn8/LyMD9uRTqcd9YuaMQr02Oiwiz5tBzTqWcrswsIC/u3f/g0A8NprrwGo7Qfsr3my+fHHHxeDioZBPB6HeaeWNmDNKt7NQIdfOf40fJaWlkQX7t27F0Dt4Mp///d/A6iFm4FaCsH9998PoK4zOUfDw8NCIHB9lstleQfH0ufzOXTNSk5A21CXhYWFhYWFxYZB04yPTsDTljRQszbpLdBCTKVSDut106ZNQlPSamcC9BtvvCFMCK3ILVu2iCVv1j7Q8DKJC2hkl4BaUjYtd4auPve5zwkd+Ytf/AJAzYujR0Wmh5T6uXPnhL7js7q7u8Wj5LgtLCysqV7BSvqja/LoCrf8Hb1fWuCPPfaYMD70kH0+n+PI+tDQkLSXrBbZu/fee088Wv5dqVRypfrXCp0Er8Mk/Leu08M2Uyaz2ayEVl966SUANS+ErImuncFn8N/8bHx8XMKYXAepVEoYFLMWy1rn1ZRxXVqCnr+u8sow3djYmDCr/DyZTAqLxb7qOjGUVXp5Pp/PcezZrdp3M3A7Ms61wHbEYjFhVSmnpVJJjm7zb3ft2iVeNNfWW2+9BQD4r//6L2HjKBsdHR0YGRkBUNdJPT09DXcm6TauFZrpAWqyQXniXMZiMcfvMpmM6FOylYlEwvE9Mj7hcFjCzuzrxz/+cVmrugQHdase/2Z0j/m3es/gPM7Nzcm/yfjk8/mG48tAjX0jo849g+sqmUxKGIx7xvz8PE6ePAmgrmf9fr/Moz4wslbotcDnFAqFhpo6BD8nw/Hyyy+LrFJndHd3y17yzjvvAKgzY/F4HLt375axIMiWcbzy+byjencz/XSLqpj7UiqVwpEjRwDUGZ8zZ87g5z//OYD6/vClL30JDz/8MADI3JgMOYCGQyPUP27lHOxxdgsLCwsLCwsLFzTN+GjPzoz1FQoFsa51wqd5f9HMzIxYqvxbeqU8sgdArMMjR44IW0A2KJPJOKodewE3L5Ox1WAwKB4FLdze3l5pM630qakpsXLpPTI+/dJLL4nXzWJbW7ZsEe+A4zE/P+8oROV1QbFAIOBIvA0Gg/JvJtjt3LlTLHJ6J5cuXWo4agrULfV33nkHP/3pTwE0eif8Htm7paUl+RuvYB43rlar4v3qODFZAn7v3LlzEoump9/W1uZgGuh1FgoFR8x9fHxc8kP0MUyvk/DdqhizLezrzMyMyBKLhd64cUNyOpjX4/P55G/I9PFnKBRy9DGVSjnuUdLVYr1gfMxnlcvlhjxCoMZkkGmjV/zee+/JGuT3S6WSyC7LLvzgBz8AUGN+qGOYVzA7O+tIrHW7K9ArdlknMmvWFajJK+WOn8XjcVk/9PJv3brlqLBNBqSlpQVPPPGEjAVQK5/BHAt+/9atW3dk09fSL/O4sdudTul0WuaKrLiuJs7PxsbGZG1RtzJf5r777hNdxT5ev35d9hSd/0bZXmsOmoZbjo++D0/faUe5JZt85coVWVvcS7Zv3y5MrE6sB2pJztxTyYLMzMy4HtzQhTf5/mah8/rILrI927dvlzxXlgL53ve+J7rmC1/4AgDgj//4j0Wef/KTnwCAHHzq6ekRfaWLIXI8+E6gvh+v5p45Tys3s4Gc1EKhIJsbE10rlYpsJJrWMi8u5UIcGhqSRfvVr34VQG2AGTKh0aAvGPTC8HHLzjcTKsPhsNDLnNQXXnhBhJnhHV21kgYPhfDy5csSXjlw4ACAGlWvNyygNpZeV4m904arLyQ1Q2LLy8uy2Hiq6cqVKzIGlAOGwZ5//nlJTKdCOnDggCwKfeGiW90ZL/tXKpVEofNnNBp1nII5d+6cyJhWrJRTfo/9ymQyMj40htLptHxPn3hyu1rBC2hly75Tedy8eVM2cK67QqEg/eEmMj09Le3jhsrNYXl5WYwmKp6enh7HCa6lpaV1reKsE0b1tSd8P/v30ksvyWbHNdbX1ydrimEGyuvw8LCEgTh+i4uLshZ1dWPzIk2vKzcXi0WRO30ykLJFvbp161aHTI6Pj8vfcm6Izs5OOcXGv0smk/IOGnxzc3OeXj6rDWCtT0yjVh/sYJinu7tb1pmWU+p7Oi2U1507d8pzGQa7dOmSGMR63ZmGgtsVPWvpp1ttNK6ZcrnsOAk1MDAg6QNMzp+bmxMnmt+jwRsKhWRP4Vq4du2afM6x8Pv9Igte6FZzL9BpAtT/hw4dkn2Re/2tW7ekf5/61KekDz/72c8A1A0f6twnnnjCkdyfTCYbqvwDNV3Hz91CereDDXVZWFhYWFhYbBismfEx78XSoGWZSCQkqZe0pU6opGeWz+fFQuRPWrMDAwNCmzExeHJyUhgTWvHak9ZJo832jyiVSuJd8rnxeFyseFqq586dk6RYWqIHDx6UhFEzVNLX1yeJ0bRi8/m8sEVsRyKRcE2kbCYh1u2osb70lW0xPaWJiQnHXUnaGiezQG/79OnT0mYe5+/p6ZFn6MRCr8N4ZrJhpVKR/tKTDwaDDRfr8v1kCbRXSA+SnjdDl8FgsEHugcYLF3XiHd9L2fGqho8O65kJlfPz8xLioXfb398vbWDNlOXlZYenxf+7VU5ta2uT59HzZBs4Bl70SUOPl77rh/JEVnVyclLYAOqOvXv3Sn/IcjC85fP5JFzC9l++fNlRift21bebgbkWg8Ggoyr8+fPnZW1Rxvbs2dNwfxVQY374HCaXalaOekYfPKFskMnVz/SamdQMkhmGaW9vl7li6GR8fFwYH7J13d3dsrcwmsBnTUxMiAyQISqXy46wWjAYbDicoD9bK0y58Pv9DaFi9pvjTf1w5MgRPPPMMwDqc3X+/HnRoZwPJjQfPHhQGHWuu6mpKWHLKDMtLS2ul0w3y1Dq9Aj2i+/evHmz9I/6MZFIYM+ePQDqyeXHjx/Hd7/7XQDA66+/DqA+58eOHRObgWHOVColTBbXaTAYdNRdWkn/LONjYWFhYWFhsWGwZsbHzTM3j7W2tbWJNUiLNZvNOgribd26VfJbmM/DRL3BwUGx8vRN1zq2r9/tNXT/2Bd6CYFAoMEbA2rVUOmVkMnRRaVozdPS37dvn3jWjK+Pjo7KM8gUJRIJhxXbrNVuxqN1gTJ91xNzB8hU7Nq1S/pEb2twcFD6RkZPF7fUhbf4Gb1LyoPuoxc3CbvlFejbhDXzws853vv373dUXS4UCsLscb5579FDDz3U4PEANc+TR3IZo89mszJ2XrMiuo9m9eVSqdRwAztQ85rMPvp8voayEXpMGK8H0HBcmh6tfoaXJRfcCm2aZQ/8fr/IEddOS0uLVI7lwQHmlQH1dcnE7lwuJx42c5l0SQTKt14nXjCTbgcoSqWSyCnZuJGREdERzEVqaWlpKKIJ1PN/gLqeOXXqFIDa2uScc00ODw/LO8gUZrNZR+7WeuRtka3QLCS9fo7F6OioI0n98OHDwiCwnTzo8vzzz8s8cmz6+/sdFZR9Pp987kVeqNt9dJFIRNYdPysUCg17CFCLbHDNUrf84he/EGaZMkoGb//+/cKSkUGJxWIN1Yv5O+4vXuah6Zwojj/X0/LysqMERDwel/3z5ZdfBlDTndSn1DW8N29gYEDklPM2PDzsmtxsJqavpJ+enuoyq7rqKrk8tTU7OyuDRqX02GOPiZHAv+VCPHv2rHRSn1rQl7AR67Ew9SBSSHUdCJ08CtQmgdUomcS1adMmUWLc7Fk3Y+/evY6L2mZmZqR/pKWbubrhdv1yS1Qzqd9CoSC0JRfm7OysKCcaPl1dXaKUOIcch0KhINQkQ5jnzp0T2l4bWXfjclJ95Qj/zz5yEe/atUv6oStw89QBL3ikst29e3dD8iufxfnTCc3sm1fyaiaf6ktX9QlEyhwp5EAgIHLLeRkcHBTDjUpWn3Ayr+XQylb/NKtje9k/n88n88T+6SReynChUJANgGH1SqUic8I+0BhaXFyUuebfRaNRkQO3pFyvYBoXlUpFZEbrBW3I8vvUi0weDYfDDdXQATRcTEpdxGsqgsGgyD/XRD6fFz23njBlx82Z/L//+z8JhejaYLqWFFAPrS8tLckmzHBYtVp1GHfRaHTdHGbC5/PJ2qKDsLCwIONMFItFufKH9d9efvllWUc0ZrmeisWiyIC+1kifngYaDwKsB4LBoMgJ5+HChQuiJ6gfe3t7ZW2xT52dnfjsZz8LoJ4Yzbk/d+6cfI/t7+rqEsNHX6a9lmrbNtRlYWFhYWFhsWHg2XF2v9/vqD5arVYlAYtMx8TEhHgcTHTdtWuXWHxMYuPFpKOjo+Kh0gNNpVKOC/TcwjRe1NbQnh09Rf18hktI1T344IPC9PD+scuXL+P48ePSf6Buwbe0tIhFSy8gGAzKu2i5a6bAi0vmNDhGoVCogc4HavNK75Ge56lTp2T8GZr0+/3iaZuVm9va2qS/9NCvXbvW4JXoz4BGVs1L6NohOuRl3uMzNDQkbSAjcPXqVUmaZF/pbUWjUaF16anncjkH4xOPxx3VpL2G9obpFW7atEmOBzPUpY9H05Pq7+8XFk9fiAjUWSEADfLJNaAZtPVgC3TtEMoFmcS+vj6RMXqNN2/elKrMnN+enh4JkTC8zr5EIhFZ25qh5Fhqen+9ShK4ldHgvyORiMgOw8/Xrl2TseZcDw8PO+5nYlXg8+fPCxtCBuTWrVsN9w8CjceUTSazWXAcdY0bvmtxcVFYAoZBLl682HDnHFBjEHiIhX3l+uvv78djjz0GoB7qevvtt+XACOczlUqt2xrkc+PxuLAw3OOi0ai0mbK3fft2SRGg3nzooYccpTfI3OnwDmV1cHDQoVsymYyjorHXtxnoenxAjdEyQ5PLy8tycIkJ2rt37xbZ5Z16P/zhDwHUwrr8vmaozRILpVLJsR/a5GYLCwsLCwsLC4Wmj7Prn+axz3Q6LZYqmY7JyUmJddLyvnXrlngfTAZlLsWFCxck1ktmZM+ePY7juvoOJi8q4prWsfYyaaUvLCyIp8zCfI8++qgUoGJuxAsvvIAf/ehHAOoeCKtzzs7OCitGrzSZTDo8Wu1Br6ZQ02qgE1V1dW2+h3N08uRJR9Gqubk5YYs4PvQi9+zZ47i5PBqNCjOob/r1IidEw0x+DwQCjqPrhUJBvBUm5S0sLDju05mbmxPvl6wB8ytCoZCj2Jhm7nTOyHrmLwGNibHsYyqVEk+fbMGpU6ek9ALbNDU1JfNhFjycnJyUZ3Ael5eXRX7p3Wm59LLopk5u5riyHfv27RNGWN/gTAZZVwTnHHLOmRvi9/uF3aPX7ff7hQWhR66foVnYZjxp8291IT32MZVKOVjSd999V/SjTpan3iAjyXxKXVqDDFm5XBaZIOuqvWuvcKeDKJTXpaUlmT+Oe2trq+hLJnUPDAyIfiEzxOceO3YMX/ziFwHUi6iOjIyIDGhm2dzHmoW+9xCo6UeOM/cKrUc4FwMDAyJ7TGR+8MEHhaljBIQV8CcmJmQsOF46902z2WY1/EAg0HR/9cEYPXdALUqjc3qB2p7GPpNx7unpkTlmYj6ZomQyKfuoLvxoRpWy2awjErKSvlnGx8LCwsLCwmLDoGn3WnuvprWZy+XEeyRbUC6XxfsnizE9PS2eNhkixvXS6bR4nHzG5OSkI5bpdhOh6RIAACAASURBVBRaH0VdK9xOPOm7V+iBac+fVjrjld/97ncll4J5TfSOX3rpJWEKyAq0t7eLVcwx1V689py88KQ5RuFwWOaE79KF4RiX3rVrl3glbGcwGBTvip4x+zg1NSXeAOPdfr/fUZDR7e4er+5AIkKhkLAWlLGZmRmRLR77TSQSDcUxgRr7xjyXo0ePAqiXxL948aJ4nhy7oaEhkRld8MtrVsss+5/P56XNZEZaW1tlnimLP/7xj+XKEX3yxDy9yPmcm5uTtuu1S69O3yNlFoTzYg71Wqb3TGZj27ZtcmSd83bjxg35HfOVDhw4IGydyS5Xq1VHUbyFhQXHHYR+v7+BCdb9XCvMI/t+v188ZJ6yAxrvJgNqbCS9Zl04k/01c9GeeOIJ6T+ZiGvXromOZV/b29tdr+Xwci3q5+lCm/wdGZCnnnrKkSeTzWaFqaM8s+0DAwOij002AkDD8WtdDgHwriwK5661tVXWFp89NzcnTCTzkiqViugj6tSWlhbH9T/sTygUEp3FMYlEIg2F/QiTufMiV0vnSZr7bltbm6xPHX1he6knp6ampF9cg2zb9u3bRU65L46Njcl7ubfk83kZ69XIZtMamA2NRqMNGyjQmDSnqVcec+aCvnr1qmz+/IxUczwelwHlszKZjBgcOgRkJhp6eVmp3qhJT/b09Eg7+K53331XjLjnnnsOQG1h0lBgwjPDYMePHxfh5nhs27ZNFgsFRydvE17f2eVWHyUWi4lCJV3++OOPS70FjsU777zjuGeNtVDOnz/vuIBPh4H0cXlTEXmlaNm2SCTiOLLv8/lkc+dC7OjoEOOB8lwqlUQuOT/s18mTJ+Xf7NfWrVsd97vlcrlVUbIrgRlOWl5elndoSp1jS+UZi8WkH5TLrq4uUVAcJ274gUDAYdTOzc01KGOgNsZeXcCqocPPXIvcJJLJZMNRX76bBgD1z+HDh6VfrCdCWn7Tpk2yTvnzzJkzsj65eerLLb0KB5khEm2A8l2pVEqMTM7D5OSk6CD+3Lp1q8yredHjoUOH8OlPfxoAGu7n0tXT2Q6uY7Oa+1phVlF3q0CvHWOutXK5LAnP2kDTGz5Qn+NSqSRzSl08NTUl65gGRktLi6NWkVfgWLW0tMi/GVq9du2aJPPqS2k599QfY2NjEvphv+m0pdNpR6J7Z2eno7yDTtHg77zQO9SNmUxGjBwamwMDAzJ33ANisZikDFB3jI6OyhwyaZ06ZP/+/fIZjcPp6WnRNXq9rEU+bajLwsLCwsLCYsPAs8rNwWBQvH9tYdKb1+EFJgKTonzllVfEgqTnyftzIpGIHIXXXoGu3MjfmW1rBqZVrKty0iPp7e2V35FuPnv2rHiSZA+2bNkiTBa9jjfffBNAje3iUXjSufreK53IbIaBmoVb0TR9VxBQG38eP6R3/alPfUpoclK26XTacQswvbSxsTHxWDgOOslXh1ZMer1ZsG/6Vl+TmQwEApLIS68okUg46NrOzk5hvfgMsgDhcFjCKjziPzQ05CgF4PP5xCvzej41k6RZD6DGOOlK6UAtEZ/zwb7mcjlhVk35yOfzItP66DrHQldYN+nvZrxMkykoFosN/wZqzBN1AmVyYWHBcey8VCrJ2mNSMOXg8OHDkjCqCx+yhAF1WW9vr4O185q9CwQC4vHypw6T6sKUZnHQ3bt3i9yRSeecPvzww6JnmFCazWYd97OFw+E1hRBWA33/odatvJuRevHcuXMSlmR/du7cKcnsHB/O68WLF2VO2cdAICDPIzOhyxd4DX2/H2VJ301oJjcPDw8L48+5unz5cgObA9SjAkNDQw0REKAW9jQPjMRiMcde6QXYF50oTtZmx44dwhpTn46OjsoeSeZnaGhIGFmGYjnPQJ0tYjrBlStXpM98V0dHx5rm0DI+FhYWFhYWFhsGTR9nJyqViliW/JnL5cQbYdwymUzKv3mUdmpqSpJFyfSQ+Tl79qx460Rra6sjMVYfv+TPZqx582+Xl5cdt75HIhGx2HU5dLaNHkZ/f78k6tEDoRXb0tIi8VBaveFwWCxpMj7rWXac45VOp8UqZ1+DwaCwO2Q7+vr6JO7Kglq5XE5i57pAGVAbJ3pl+nZ6fUsy4F4MrtmEStMjj0QiwthRNkOhkMwj27lp0yYZAyKZTAqrQVaBjMLQ0JAkrrMwns4d0mylyfDoo8trgSmrfr9f2q7v4uIY8HqYgYEBYXDoSV+8eLHhnh+g7pVOTU2JnNPzikQiItuaQXNrY7PMAWWnWCw6rnPQ91jRS7548aL0X+fE6IMWAIRh+OxnPytjyST3EydOCBtIvRUMBl3z7Zrpn9sdeWa+XTgcFuacLFSpVHLckVgqlaTNTF7ns3K5nIwTGdl0Oi1zp5Ny1wu6j+wb9V04HBY9SDayXC5Lrgv3hUcffVQK3PGqB/YnFos5rs/p7e1tOIACNB7r1snlXjCwOrfPzG2JxWKiK6lT9+/fL4n13CPa2tpkDJgbSZbL7/c7WLB8Pu+49b1QKEiOmBcwDyvk8/mGpH+glpjMvlCXjI6OyvzwGcPDw5JbxjFikcmrV69KH7hXptNp0c/NFg5tOrmZm1upVJLB4KJpb2+XQeeCTSQSchfJr3/9awA1CpnCzp+6dgyVrO6smYVPQdO/8zKJq1KpiOByoru7ux3hmmQyKcLMSRocHJQTCGwnx+jgwYMSemC7l5aWGk7oALXFb17G1izMExVLS0sy1vokl3la78SJE0JD8ueePXuEhuX3dOiOm6Ou0myeUtMnEbyqMuq2oRA0fNra2sSgYVv0ySSGWsvlsmygDN1x3u+//34Jk/DvlpaWHHcgacNnvS7YjUajkvDJjf/ChQsyHwxd7tq1SzZBGgPXrl0Tx0XXsgFqskh55EbZ3t4ucq43T/PUpZc1bnTtECax3rp1S95JRTkxMSHyzI1m9+7dEjagAcjNpVKpiG768Y9/DKCmsCn/NJh1FfXbtXGt0OuebdcJuDRouFFMTk6KXqQeKZVKYtByXjn32WxWNkoaT5lMxpFYGwqFHHPnVViI7woGg6LT9AbIhGT2e2pqSsaeoZG9e/dKHznfunIzZZz7ib6Pj+Oaz+c9D3WZ+9Hs7KwY2DTSFxcXRfdow48yRUfz6NGjYpTT+aD+uX79uhg+OmnZDGvpSvFewDzNGAgEHCfnrl+/LmuKMtnf3y/3rbEvs7OzYpjzpBeNWL/fLykx1CuxWKzBWQUaq5mvBjbUZWFhYWFhYbFh4Nnt7MvLyw5aXyeIkkE4ffq03FtFy76zs1NoSH6PlBdDL0Dd8iuXy8K+0PJzqxbbDNy8HVrx+k4meo+01ru7u4XdoJdZKpUa6jUAaKhLwd/R6wkEAg3jyvevVyIeoat80juanZ2VMaCHePPmTQknsI8HDhyQUA//ll7pjRs3xLOjhx6JRBrYF6DxjhWvPGh6WxzHQCAgDI4+Gkkmg22+fv26tJXo7+8XVovPpVcSj8fleRybqakpYVz4fc3aecX0mEehw+GweO7s69TUlLBz9J6z2ax4y/xeOByWPjJUq+uPuB1dp5epWR6vk37183WSrz5qTk+eeqhcLov3rOv50Gtku8l6nTlzRkK3pOUjkYiwgZpm97rcAqGPCZt6oVAoyBwyHDI/Py/hH+ratrY26Rv7z3U6NzcnMk4GQidIm+UkAO+PenMtaDmlLpiampLqxC+++CKAxtvWDx8+DKAmu2Q8yMAz9PWxj32s4RAFUGOF3A4TmOyrV+A+Nj8/72BEZmZmpO1kPCYmJnDs2DEA9bDWgw8+KMwtDwLx53vvveeomK6PxJMF0uyrl33Ulam53iibqVSq4f38HevycJ0GAgFH9XSO1a5du0R2daqLWT5G6xpiJfJqGR8LCwsLCwuLDYOmj7MT5XJZLDl6LYVCQSxWepZnz54VK5dW8YEDB8TL1EwDv6OZHqDmHbjdbbMejAgtS/1seglTU1NisbJt7e3tYpXqonjMCaHVTw+mUCiIxc7nao9SH+X1mg0xx8vNE6pWq8JakH2bn5+XOC2T7Q4dOiQeF2/E1jcE06PTye5e5w7cCTqBm23RngTljazW22+/Lf9mm48ePSrMJH/qO2M4PrpYIaHHdr1ye3R+EueHHlc6nZaEbHpj4+Pj0m/mgrS1tck8kuGgjEciEZFbIhQKyRi4rRUvwefqu7qIaDQqeoI/e3t7JSeEOR/t7e2ip+h1M7/g0qVLsj45v21tbcKQaWZrvY54E5VKReSHemRhYUG8arJUvb29kkdBpqCnp0fWLGWR7V1cXHTIfyAQcOQPelH1/nbQ696sbL68vCxMK/eJXC4n+XNkyvv6+uRv+RmrbQ8NDTmqji8vLztuKdcMiNfsq2bsOd7c7+LxuMgoCxm+9dZbMreUQb/fL/1gfgyTvMfHx4Xp4lqPx+MNubRAbc2aB4G86B/1SiKRkOdzDM+ePSvyp9tBtk4Xx6XOZDI0f953333CtOq7P3VOMbD2SIhnoS79cl1Cnx0jRaeztZlcuHv3bqG4uNlQYCORiHxfhws42Lp+z3ooI53MZVaI1HVvKAjz8/PSNlKR4+Pj0h9uopzURCLRcMqA8HpTXAn0QtNXZnBz5AJOpVKyoVDZtra2Cl3JDYXhvaWlJcflp8Vi0fOaPSuBTlLnz2KxKAa3DqFSodIo37lzp4QxaTxwXrPZrIyPVn5uJ67WC3yvPtVF2YrH4yJTWsFSebKdW7ZsEUOHilond7tVR9dXGqxnvzQop7peCtvBjSCVSokBw89u3rwpcso6PjQwkslkQwIzUOsfjSyOqb6yYr3g8/karsbhT/OC0b6+PocRXiqVGi6CBOrhoEwm03DpI9+lZeduQYe2uZ6AukGmL8TlvzkvuVxO2swx4R4yMzPjqJWVyWQc1am9voTVDT6fz3F6taOjQ4xVfYCC8qUPUPBvmdSuHUiGNnXNNc6t256yHggEArIW2Zfl5WVZW5yHtrY2STTn9zOZjMgb5VTXAKRM6JpVXt1eYENdFhYWFhYWFhsGnt2W6PP5HFS3PoKt634wIZTeVSqVclSLJVVWrVYdFYG1d3e3oN+pqVIzsVRT7tqjINND8Dtux/HcrFivLwh0g9/vl7boSq7mXTi6DgUxMjIiXiVZPo5Ja2ureCJutKtZmXc94Mag6TvKzCPZmzdvFrnT4TnOKeloXZXVLXRnXtZ5N5g8n8/nWB+xWEzaQg8qn88Lm6GrZ/NzfQSf31lvdudOcLvbyS3JUc8R54ffn5+fF8+fLCR/agZCv4fv8DJksBpo1pnsBn/29vbKWmU6gc/nE+aSY6HljjpZM65m+YG7Nb/mnJXLZfH0GfaIxWLCFrAfo6OjwkSTDSGq1WrDYQagsS4S+7+e86jH0RzTSCQiLB31YrFYdFTgzmQyjvpt+jNzjeuLbXXy/Xr2U++LOhWF7ebPUqnUUNcNqLF21DHUOWx/Pp93HJbS4dhm5dMyPhYWFhYWFhYbBp4yPmbxJp0DQ6tTMx/0sguFgljvZly7VCo54pWaabnbzI9+p76xXbdR57Hwd2Yyplv73dgArxOa3w9mzpbOF9GsgFmUa2ZmxnEnDb1SzYK5ec33gj3Q0F4L58nn88mc6jwB00PVMJkrneNzt3O23O5hM9dKa2ursFrsazQalbaaLKyujn63mQETbu832ahCoeCQyWKxKH0wK8Lrv9XyuR5H81cCMwcukUiIt8z5isVijirW1WrVoYP4d1oOtZya4+nGft0NBAIBYeCYw6IPezAXr1wuy9xyzeq+mXeAVSqVe5I3eTs9R11Kxsfn8wnTxXVHBg9olF+gUWe5HVe/WzLrtk50IVotr+Y9YlrHmrmDlUrFwdZ6KZOeGT5uiZz6skJzwQKNmfy3u5JBny7QIaG7rYQ0dCiPStQ8PWF+/3btvReLcSXQC0eHhAiGC/S8mbS6TrA1N6V7bewA7ietNMw6Q7f7Hp/ldlrrXhjmGm40MREMBhuUFFDr8+0qhH8Q5oxwC0mZThPDPW7fB5yJn7dTrPdK15gnaHQ1ZaJarTacAuLvbmdw3+4UjFdJo2sF5yIajYpBqo0x0xjXn5tXy2gD3Q33aj61IWuGWfUeoZ1+s62UhXA4fEcj/V5A79O3u34IaDSQaNy6HQJZT5m0oS4LCwsLCwuLDQPfaqwon883DWBs/ZqzbtharVZT7/elD3H/gI9+H1fUP8D28QMOK6e/ge3jBxq2j7/BR7F/qzJ8LCwsLCwsLCw+zLChLgsLCwsLC4sNA2v4WFhYWFhYWGwYWMPHwsLCwsLCYsPAGj4WFhYWFhYWGwbW8LGwsLCwsLDYMLCGj4WFhYWFhcWGgTV8LCwsLCwsLDYMrOFjYWFhYWFhsWGwqru6Wltbq11dXevVlnXD7OwslpaW3vcSk1gsVuXFqR82TE1NzaykCmc0Gq2aF6Z+GJBOp7G8vLyii2gSiUQ1mUyud5M8x/z8PDKZjO0jPvr9AzZGH+Px+Ie2j9lsdkV9jMViVV7I/GHC4uIicrnc+/YxHo9/KPfFhYWF287hqgyfrq4u/NVf/dWqXn67SzvNz253IZnb36/2lta//uu/XtH32tvb8dWvfnXFz9VY6S3qd7rV+k5/+379/Zu/+ZsVlRRvaWnBs88+u5KvfqDwgx/8YMXfTSaT+LM/+7N1bM364O/+7u9W/N1kMolvfOMbTb9zNbes32m9rhTf+ta3VvS9ZDKJr3/966t69kouaFxpu/W4uF0Mejt8+9vfXtHzAe/n8E7wskL/SucQqPXxT//0T9f0Hi/3gNXiO9/5zoq/29bWhj/4gz9Yt7Zo3KnPq72g9D/+4z9W9L329nb80R/90aqeTbzfvmheWu12q7zu82r6+E//9E+3/cyz29lvB7OhbgIbCATke8vLywBq1ihQuwWcN0jH43EAQCwWc9ysfK+u3uBNuvo2ZP5b31bLm3nNm+bL5bLccK4n3+zfBw1um4HuE+B+gzvn0LxR+YOG292wHolEANRvSeb/i8WiyCz76/f7RXbv5a3JJtg3txuQtfzyJ2+p9/l8jtvc9djw3+u9Kd0O5jtvt2FSTvl9yqv+jD/1eNzpxu+7BfO2daAui3rT0De1A/X+cC71syqViuO5el7vNsx5LJfLrrd361u+9c9KpdLQzw8i3PZFQq+/UqkEoC577Je+uZ232YfDYVe9/EHQPbdz9M31RlkOhUKiR2kTLC8vyxzz+2vtm83xsbCwsLCwsNgw8JTxWSnlSmuN3nIsFhNLll7zzZs3AQCZTAaMEcdiMXkOLT/tja23l+nmHZueUrlcdlji0WgUiUQCQH2MZmZmAEgsGQBQKBQAAIlEQpgR05txa8d6g23mvAWDQQcrUC6XxTtZWFgAACwtLckzuru7AUDGIRaLSX/5d/x5t6HHU/eL/9YeNdufSqUaPrt27ZrMI5muSCTiGLu77X1p+TTnzI1C1p40PS7KXigUcjCXQH3e9HNXE0JbC9w8W5N9LRaLjt8BjcwUUF+nPp9PdBLnOZ/Pi5xqZki/d73gxu64hQaoO/XckFHlPPH/8XjcwcTmcjnHGqxUKneV9dHjyH6zLcViUfrI/rS1tcm8cc74/UKh0MDA8zOTXbiXTIheb0Cjftc6n33KZDIA6oxPuVwW3UO4sTv3mu2h3Pn9fse6KxaLMoetra0AaqkYQG2+bt26BQCiVzX7ynlda2TEMj4WFhYWFhYWGwbrkuNDi05baLRO/X6/eFMdHR3yvfPnzwMA3nvvPQDA2FgtV7e/vx88SbZjxw4ANa+FXhi9lmw2K7HA9WIOaGVq74Tvpzfo9/vFiu3s7AQADA8Po6enB0CdDUmn0wBqTMHVq1cb2t3R0YHe3l4ANc8GqFnEZix/PWB6In6/X6x2t0Q1/juTyeDGjRsAgAsXLgCos3dbtmzBpk2bAED65ff7ZSzYr3w+Lx7N3WC13Dxq07sH6h5YV1cX7r//fgB19vHatWsAal4zZYH9iUaj8rfa27kbuSJ3YguIWCwma5GnNrq6uoRtpByzr+VyGbOzswDqjOXy8rLIMuU3n8+vK3un5U/nqXD85+bmADTqBM6r3++X37F/ZJS3bduGLVu2AKiP1fz8vDxX5zrdixy8UqnkYEkDgYC0j/q0v79f2m/KcygUwtDQkPwtAExPT4scc02Wy+WGXLD1gp4/vpfjTMY4k8lIHymbkUgEmzdvBgDRLRyTqakpXL58GQBw5swZeX5fX1/DM3Su6N1gt/S+qNlzoDYv3C84j+3t7cLOjY6OAqjnu/h8Pvke5XhpaUnmmfMeDAYbdPl6QufO8V1aF/J31BeLi4uy9vr7+wHU98yJiQlhuebn5wHU1p8ZOeFc6t+tBJ4ZPjqhUTfATGKNx+MyYRyo69ev47nnngMA/OQnPwFQDyV85Stfwb59+wDUjYBYLCYLhYOoJ1VTY81CbxaaSgVqCp6ToxNah4eHAdTpO32ck22bnp6WNroJhKkQYrGYKy3qJdySsEOhkEOJTk9PizByfpeXl8WAu3LlSsNnoVCo4d9Abby4YLXBwHeZ4ROvoGXCTBgE6ossk8nIu6kw9+7dK2PAPk5MTMgzBgYGANSp91wuJzKg38/+8lleJ2K6yf3y8rLjPaVSSeaDRurk5KR8TrnlOExNTYmMUgbD4bDMI5HP5x3hBC/m0c2h0nqAfdDGjmnc+Hw+Rzhd6yjz2O7Vq1fFoOfajcfjYgxyrr1ak27Ghg4nU2Y5vu3t7eIY0hCIxWKiXy5evAigLqfxeFxkfP/+/QBqjpm5FpaWlhxj7PXGWa1W5X18R6FQEJ3KNmcyGdH9u3btAgBs3bpV+m0a6LlcTgxzOmHhcFjWHQ0/rVP504s9w4Sbw8x1xH51dXWJAccxuXnzphiiNOSod9ra2sRYoI65desWrl+/3vCulpYWmEftvZxHnRJAhMNhWVM0VIrFIi5dugQAeOedd6QP1D/s889+9jMANbmlAzM4OCh94drlmHZ1dck7uBZX0j8b6rKwsLCwsLDYMGjaTXFLkNSJx/ycnlRHR4dY6rTsR0dHhcqjJ/PAAw8AAJ544gkcPHgQQN2Tu3Tpkljv2uPSHqFX4DNLpZK8k1b4bwp5SV+BmvVNepIeZWdnp7R9amoKQN07e/DBB+W5DPdduXJFLGGOVV9fn3hlJvPkJUwKX3tg9DpmZmbEyyK7dd9992Hbtm0AgMceewxA3fKORqMyJ6TU5+fnxVKnNx4KhVxDXV6G9nw+n7SFz41EIjI/fP/8/LzIFj2OtrY28VqOHz8OAMJy9fX1SShWU9WkbknJlkol8VoYNtJhhWb7RlBWdCiYyYKcl97eXvGMKVOjo6My35xjfjY9PS2yzc96e3uxdetWAHXvVcuQyfw0M5dux3x1KQi+i2zxpk2bZJ1xDpeXl3H27FkA9fXJPu3YsUO8aIZZfD6fyCznTYeiNUPqhZzejukhKCfsY3d3t7SFYzIyMuJgCN566y0AtXkjq8f2btq0yZEsWiqVHGkK6wGztEAwGGxoA1BjEPbu3QugzvgsLi7if//3f+Vz/VkoFBJZZLQgFArJmDGBNh6PS9+0LvUyUqCT7vncTCbjGO9wOCz7CuVzamrKsT75rFQqJQwzZXthYQFvvvkmAMha37Jli7yLY6IPKTTbP7fQfbVabWDwAGB8fBwvv/wygDqr/tBDDwlLNz4+DgD45S9/CaCmhx566CEAwM6dO+VdHBuuz3A4LLp1NX2yjI+FhYWFhYXFhsGaGB+35NZqtdpwdA2oWalkemiVdXV1iYVKa3Z4eBif/OQnAQCHDx8GADz55JMAahY7rXLGa1977TWx+Oihtbe3O6zitSYg6nwlPqtcLktclu/WyWTsZzKZlPg6rW56lvp59GA+8YlPCGty8uRJALUYKPMJ6J0Eg0EZL3qepVLJ00RZn8/nYJOy2azEjfmzvb0dR48eBVCfL+2xsO1kqwqFgjAlL7zwgvyOiaRuV2i4FZDzqo/mEd/29nbXBN3t27cDgDAaQM2bBuq5MJTroaEhkdPTp08DqHlYTzzxBIAaIwbUEm/5Ds5js0yBWx6NuRZyuZysS/YrlUoJO8tDBa2trdizZ09DvzWDyWRRem3ZbFYYESbw9/X1OXL71iqnbsUQK5WKozBkqVSS9zNX4siRI8KGcO28/PLLwtKRLWKpBZ1/Re+4ra1N5ph/F4lEHMfkdUJnM9D5NJqtA2pspFsOHPUi5ykQCDjyzciqtrS0SNs5Jj6fryFXj88182/C4bAnSd26xIMuvsfPTD2SSqVw7Nixhu/9v//3/2SdUV7JNFcqFWFdDxw4AKC2j1BvM7qQy+UaDqUA9SjEWuBWFqNcLjvKlaTTaXkvZS+TyUg0gLolEAjgmWeekTEAIIyOzsHSCdLsI/NjIpGI6CV+r5nrNdyKS+oSCHwnmW7+bm5uTmTnc5/7HADgi1/8osgp2SAyP6VSCR//+McBAF/72tcA1PQl1wSZn0KhsKY8Lc+yZPUAUzh1Mp6m3vlvCv3Bgwdloij0XHTvvPOOTCaV7nPPPScTQBps3759jqq6uibJauAmwLrdnMDBwUGZYApmpVKRZEiOgw7DUXmy7zdu3JBFypNs4XBYNh2+a3Z2tqEyqf7pFfRJHN1vLlyO686dO7F79+6G/ly8eFHaz76SZu7r6xPKncZgtVqVpDz2S59a4bu8MuzcqmJzDtrb2yXsRjksFAqyyLhpLCwsiIwxrPXUU08BqBmwP//5zwHUF/Hly5dx6NAhAGgIpZmK0Ku+aXkww76dnZ0io9wohoeHZV4Ydjtw4IDMmzYIgJrhe+TIEQB15TwxMSFGE/sIwLHuvViLuo6OWeulWq3KfFIBjo2N4cUXXwRQ1x2jo6PyOQ1z9rNYLMr3uK6TyaQkt3OMWltbRQ70qaBmDHRzTS8vL8smzA0xnU6Lg6VDxzRgPPvrOwAAIABJREFUuKE988wzsqGwzdSnXV1d8jwaAKdPn3YYknpDYTgiHA57GpINBoOOU4Wtra0iWzSuU6mUfO/dd98FUDOKmKT85S9/GQBENl966SXRRUzgPnjwoDgtOlxiypGuw7YamEm+HO/l5WUxSDmf6XS6IbwPNBq6XKd79+6V/Y3ONPXT8ePH8cYbbwAAHnnkEQCNJ730yUVzX16rga77R92lq2Trunx0FujcLSwsSCrEb/3WbwGoOVaUXfaLcrBz505Zd5znYrEo40HZ1bWLVjNvNtRlYWFhYWFhsWGwZsbHtLLcPLNCoSDeBb2GYDAo4Sn+7aVLlyQcRA/03LlzABoTRM1aE0BjOMurI6VulqNOmCOlvnnzZrFGyV6cO3dOvAh9nxO9jbfffhsAhBXq7e3FT3/6UwDAK6+8AqBWT+R3f/d3G/q0uLjouAvKqxCQW391lVMdEgJqljq9Jobnzpw5I14A2SqyQrpCJ63+RCIhiadEoVBoCHF5AbcK0/R4OJ/t7e3iZfL478jIiIQgOd5Xr14VxooeNUN93d3d4vkwsbRSqYg804srFAriyXK8vGAKzD7Sg6UX1traKiFmzsXY2JjIow7fksHhsVO2NxQKSXiSrFAul3McMdVMr5msu5a+msnoOhlc30VF75E6Z2FhQTxfXTOK+oRhEOqj+fl58aLpOT/44IMiB2RPgsGg6DN9lN+L9ch+5fN5aTNlrlKpNFQ+B2o6kZ8//PDDAGphVXrQDIPpkhScL+qk2dlZR0hM1yPT9cO8DOfxmUA93J1IJBrKegC1cLJZKgOAJL+ythZD8d/73vfw0ksvAagfIhkYGBD9yr2lVCrJe00Gb7XQsgm4V6Lms7u6uoTNoF5Ip9PyPe4llUpFGEjqJx6AuXDhgswF9fKhQ4fwsY99DECdQSmXy9I3/mwG5t1v1WpV5IOfRaNRR52zdDotn7N0zS9/+UuZV44f+x6JRET/fO973wNQm0PqNa6DQCAgepf6dCVzaBkfCwsLCwsLiw2DNVEkbtasW3Gtubk58R75GZM8gbqXefHiRYlhkuGgF5NKpcSi1ccqad3Rom9paREr0+0uorVCF96jNcr27Nu3TzxDevlTU1PSTn3MkF4oQYs/l8vhRz/6EQDg1KlTAIDPf/7z8j1d7I6ekNdF/XRVYTMptVQqiVdCK3tmZkYsec7b8PCwzC0ZH3rW0WhUxo4sS39/v1j5ZPt0HpXX1al1DgX7qJOqzUJhmUxG2sDfnT17VjxO5ocwl+DixYuSuM0cnr6+PpFTejY6d8hMClwL/H6/4+/1/zULylwDJppfvXpVYuVs56lTp2QO2A9ix44dIttc452dnfJcfTebbp/ZptXCvOPH7ch3LpcTOSJDNTg42MDIsZ+cO65PtntkZASvvfYagDqbEA6Hhd0ju0tmSb/fK+jcLM4D5zAej0tbuI7m5+dFB7Lsx8LCAn74wx8CqDOylPWHHnpI2AD+DAQCjmr6fr/fkRTrVeE7nVdjVqPXewYLGHZ3d8scMXcklUpJW3lU/9VXXwUA/M///I/jdvrz58/j9ddfB1BnT7Zu3eroUzN6x+fzOUq66Gfq+9I4f2Qkl5aWZE1xLtLptOQFcY2RcX322WcdFbu3bNkiupprYHJysiFCAqxdZt0ONbk9NxAIyPt1pXfqGq7T5eVlYRWZmM71+uKLL0oxYzKTn/zkJ4WR5FpMp9MNeVIrxZpjQ2ZCpVuS0ezsrNCPFFifzyed5YYSDoflpAk/o0AMDg5KaEmHk7g4zITm9YKuPkwlCtQNNG56S0tLePDBBwHUlc3Nmzel7aSjmbEO1I0H9iEWi8lzuSHdunXLkejrduJlNTCF1+/3S5spRIlEouGUHvvDRUdq9dixYzIupKj14mM7qaSr1ar0kRuJHuP1urJCV6emctLjTdpUl/0nNX7q1CmZRxoFpG3n5+dFZp9++ml5Pp9BZbuecqrHzK2aMttAAzoQCEiSNufsypUrIo/6ChWgttbM9dze3i7jyY1qZmZG5tHLZFi3SziJ2dlZmUO29xOf+IQoVPZlfHxcNgIqYIadT5w4Ic+jY9LT0yNjwzHV8+pVZWpzow6FQvJsOnRDQ0NyGpQJ9NlsVjY7rsnx8XE5HUPQyOvq6pLNiJvv9u3bG+pMATU95kXtJQ23MTLTE27cuCEyxvd2dnbKHqAvszYvBaaRcPjwYZl3Ol+vvfaaJEbT8G1ra5Ox9Sq0bs5jJBKRd3DTbmtrcxjp5XJZ5pHzE41Gpa1MG9BhMIbuuJ67urqkv1wf6XTacWLV7TLT1UKfzHOrAcV2s887duyQuWM7gsGgJCs/++yzDd9//fXXRYY5z48++mjDgSH200zMX0n/bKjLwsLCwsLCYsNgzXV8TI+nUqk4jiAvLy+Ld0UmQf+OFuL999/voDzJdGQyGWEJdF0Yene09rQnT4tyrYyIthjdvEx9JwwTsJiENjg4KP2iJwLUa4swoZKMzwsvvCDPY+XRoaEhYUHoGRQKhQZL2QuYrJ1mXPTlbxxrnSDK5FYeF+3r6xOPn9Qzw0DxeFw8VVr0ExMT8jmZEn0Rq1dwS8I3E/SKxaL0l+G67u5uYbB0jRtSrJQLjg1QYxiAOltw6dIlSS4lW5BKpWSM6aF77W2Gw2Hxrvi7bDYr4QL2cXBwUKhzzu3JkyfF4zarLufz+QZvFKgdO+W6ZDi3WCyK7LvVaFoNbue5cQ3o++P4XY7/fffdJzJJ7/H69evSNv7U7Wa4iAmzHR0dMse6DMd6Xfio9Q7Xgr7smB6/TuQmQ0c5zeVywh6wjhHrpLW0tIgHTRboyJEjMo4MKywsLEh/TXat2b7xZygUEhnT9x9SZtjX/v5+kTcy/Js3b3ZUCmeI/Qtf+IJ8n2Py5ptvii7l9/T71ytk6fP5HGHEdDotYUZ9WIL/Zlg8lUrJPHIPpGxfu3bNUTKiWCwKu0PoysbN1g1zGyNdWsKt2r5Oe+D+pWslkXFmP6mjyuWysEHcF/fu3etIhSiXyyI73EdX0j/L+FhYWFhYWFhsGDR9nJ0IhUJicdEboqcC1GOZZ8+eFSub1nsqlRILncmjPI4YDofFMyFr0tLSIt4ArT19VM+LAn9uReHogdFynZiYEKaH1vq2bdvEmieTkc/nhSFh/g8TpG/duiX5TfzOwMCAeHH0VMPhcNNHLt8Pfr9fnk2vq1gsOjy19vZ2scbpUV69elXyDlg0jmN35MgRh4c+NzcnMqELGJpMopd9AxqT8Onx9/X1ybzQi+zs7JTx5lxt375dvDd6T/Swnn76aamySs/yjTfekD5yLeg7pby6EdpkH3TCM8czFotJ28nQ7Nu3T45q8/u7d+8WWSZbwmqxL7/8srAFXK/lclmYK2K95FODa5AMVKlUkv7Rezx58qSUJ+Ax4GKxKIwXf/I4e09Pj3jUnPOZmRnxULn+o9GopxXTNTRrxzEmU6CPqVPu5ufnZb70/UXUmdSTZFrfe+890UuU+T179jgq/k5MTDi86/Uon2EeQU4kEqIPuf7y+byww1xbra2t0h7m/+gq/swfpX6emZlx3CJQLpc91zfmc3w+n4OJyOVywjKSQR4aGhK2jTr/zTffFP1BeWdy+/j4uOyVnDO/3y/MkM7L4zh6OY9a51B3UDdcvnxZ1orOlePf6DspqTuYZ0eGaP/+/VL6hDoqEonI/GsW0tzvV8LGrvlU152yurnYBgcHRbmQ8j937pzQ8Ky0mUgk5JQQTzh95zvfAVAbACZ2cZPNZrPSSQpxOBx2lHP3IoSgB5WLkzTz+Pi4bIBcfAsLC1JKnYojk8mIomJ7edpiYmJCxoH9bG9vF4XNie7q6nIk5Xq1wehTMzq0B9SUKRWlDrVRYbGez6lTpyTExfYxjBKNRhsqNvNdfIdZkdr8nhfQIVnOBTe0RCLhOC2Ty+UcVV2TyaQkCDMcxLFpa2sTBcPPRkZG5N/ceNajb2Yf9VUm5skcoB7Wev7550VWOZ8dHR0NiYtA3UAMBoMyj/o6Fso013UwGPQsZOmma3SVW85lLBYTeWPfT58+LTVA6Eg8/fTTolB///d/v+G5L774opw8oSEQCoVkE6E86ORmr6HHnjJDI0aHC+gEptNp0T10Rsrlsmyi3DiZoP/aa6/JXDOcF4/HXVMX+K5mw5V3gq5bBNTWCfvNebxx44YY33rNUj5pKHEcSqWSJDLTwNixY4fjegy9Trxei1o+zOsw0um0jClPMR06dEgMM6ZPTE9PyzwSWo9Q93COjx8/LqEjHjpJJpOONJJmTnWZJ6b1Jaxcizdv3nRcUjo4OCjtZf/OnTsneymdFtav27Jli1SY1zXBaETquoBrCTvbUJeFhYWFhYXFhkHTWbLaUqZXSVq/v7/fcTGa9q75PX1klBYivY1wOCzvIAU4Pj7uuMQzFAo5qmY2e9xb969cLksbaaWOjY2JpUrWRl9SynDd1NSUtIN/S0ans7NTjvIxOfbdd98V65neuT4W6TX0cUS2k0zT9evXhYbk9xYXFyVpkHTr9PS0MFaf+cxnANTZrRdffFGex/HSnjT76vP5hDXwKqGS0GygyRZkMhkZW87x22+/LUmG7LdmfMiU8LknTpyQtv/4xz8GUKvETfmkbOpwntd3rWkvTLMvQI1F5O9I/7/00kvifXF97tu3D48++igAOBLSu7q6pM30Tm/evOmoSRIKhRxepm5fs/D5fA13EQE1PUDGh7Jz6dIlCeuxLs+Xv/xluTiWDAHlu1qtio7hGA0NDYkX7cb+mlWlvYJOSqW+LJfL0jeWxdi2bZswWPze888/L0wBE/Q5h0tLS1J6g7K5detWR/20TCbjWkXdi6RuN1aJfQ0Gg/JvzZBwfVLWWlpaGlIOgHpUYXp6WtY2Q0m6fpy+WcAtVcIL6PQAHeJif/TlxkD9kAhQDwW1tbXJPsc54N6yadMmPPDAAwBqFZCBWmjMrPfT29u7rqHnQCAgz+d8Xb16VVgonRJA3c8++3w++ZzrmQx5pVKRPYO6ZMuWLTL/jCpNT0+vSa9YxsfCwsLCwsJiw6DpAoaE3+933PeijyHS2puenhZrjZ/Nz8+L98/YJD2LXbt2iYXOqqrXrl0Tb4Xx71AotG7eF1DrLxMpmY+UzWaF6fmd3/kdALU4O9tJ76mzs7OhcB8Aqaza09MjXhzZoJGREUeMvrW11eHlNmvJm0f2K5WKWO18r644rW9SJntA9PX14fd+7/cAAF/72tcA1CtR//SnPxVPhaxQKpWSd+nkWDMp1+viafl8XvpGb2p2dlbax9yrX/3qV8Jqsc1btmwR74MeG+f4zJkzMlbMU7ty5Yr8rT7Cax5D9Qocu1wu5yjq1dHR0VBgjP1iP8gM7NixQ/JHCH728MMPyzjpqs5kJXUfKaO6aJpX/dNJqZTDzs5O0SFk5XK5nOgTHhxIpVLCeOi7t4DaXHLtMndtYWFB5lxXH9clM/RPr9Da2irrje+6dOmSMBkc/0AgIGNN2f3hD38oLNaf//mfA4CwXFevXsXx48fl30Dj/YJkcG/dutWQkO9lH/WdcuZ9dfl8XvQBZa1SqQj7eOjQIflbsq5mtGBqakpkgXp3//79slYpH9lstiGysB599Pv9IqO6jAJljuzOwsKCMFZM5O7p6ZG9lDqLe8C+ffuExSRL8vrrr4tO1WvdvDevGabZzP8Lh8OOfam1tVWYU+bK9ff3C0upD0aYh0T48+LFi3JYhnj66aeFLeJ8RSIR13sB3w+W8bGwsLCwsLDYMPAsx0cXMtLWGD+n9f7GG2/IsUNa27TigLp3+elPf1r+TyuQx6QnJiakECBZpnA4LBa/tmy9uJcEaGQKNAtDj4Le0czMjJxuotW7detWKaFOj4oeic/nE4ud1u9zzz0n1j+9Pn13D8dNx1ebgS78SNZC36fCd3Deent7xXuiFzM8PCyfUw548/fJkyflM/Y7Fou5Fpzy+rSM9i6BmlfINvMY6LVr1xysW7VaFY+KrN7+/ftl7CmnPD0SiUTEk+R49vb2St4Fc2L0KQjdRi88TT12+hg7UGMpOI/s1yOPPCInJelZlkolYT247uiBDwwMCEPEW8zn5+fld3xGMBh0ldVmoa8DoBdNNqZSqTiu5NC3mTMP5LXXXpO8Js458yt0WQ0+d3p6WuSEslsqlRzFRPUVE170MRKJyJixXyMjIw1FQQHg6NGjDfesAbV8M57w+tSnPgWgfoJrYGAAR48eBVBnwYrFosgxf4bDYWG42Fevi4tWKhWRLerUfD4va1DficaxJ9N16dIlYazYD33iiWPHvqZSKVn3OjLgdSFK89STXgucp6WlJWEbyZZqFpO/e/LJJ6VP3CO4p0SjUdGp3As3b97syK3L5/OOSIgXua9a7pl3Q524vLwsTA/1Xjgcljlhbt3s7GxD4Ur9WSaTwa9+9SsA9fm6fv265OzpfMK19KVpw0efnTcvs5udnRUjgKGdsbExWZQ6Gdqk0KiMfD6fXD5HBRSNRhuSZAkOnhfJo24XnfLfnOienh555y9+8QsANdr4+9//PoD6Yh4YGGi4sBSoJ5+l02mh1bkwX331VVHeFO5oNOo4mhwIBJpStqbAlEolaR/bHg6HRaBZk6FSqTguKdVHSKmo//Ef/xFATWCPHTsGoH4Mt1gsikLVNXbWKxGPG6UuLUDjTV/EStlMpVKSEElZ7OnpEQXEDYh1JyKRiGyalI/p6WlZ+PpOObc715qB+feRSETGlPJ59uxZCQ+zLfqIL9t04sQJuczRDOeUSiUxiDnHmUxGxpbPbWtrE4Vm3p+zlr7qsAF/cg3oUghUhvxea2urtEPft8Y20OijnkgkEhJK0Unp5r1nuk2EVxuormfDdvGI/YkTJ2Rdcj09/PDDjvDw7t278YUvfAEA5EgwQ18LCwt46qmnANQNhsuXL0vYSNeXoY51uxy2GejkZn1JJ1DTh6YBq+u3cM2eP39e9CH7yk1Tt5WJ39lsVmRBl3rwqgq+CV0KgzqVP7PZrKwZ6tHBwUExcqh3WltbG2oZAXV9e/36dZkrvmtwcFDmjIZxLpcTY9E8/NMMtExwrfCdnZ2dDZcC8yf3OTr/MzMz0jb2Rd+xxnHgZ7lcznGnYrFYtMfZLSwsLCwsLCzuhKbNXVqR2WxWqFFatkD9iBstv2g0Kp4kPeNyudwQYgDq7E65XBZakHRnKBQSD13f5m7S616iWq2KZcnwVnd3t/SLBbaef/55odVZWOvo0aMNx+4BNFRhZrs5btFo1MGydHZ2Op7Bdq0V2vMCanPEcBst8WQyKV4Tx3xqakqscJ1IyhCJDhMANZr9kUceAVA/cnv69Gl5F/vd1tbmSMr1CtorpnzoQpf0IMjQdHZ2SlspwyMjI+KZkp3jPO7cuVNYPbJ0V65ckf7QE9N986pyM8G26DAJ266Tr4m+vj6RZTJZusAoQ9D6xm4+j/KRSqXE09ZJ926J2/qetNXATCDW9+bp5Gmz0GAymcSlS5cA1OX00UcfFVaP4Dzs379fnsHDBZOTk/I8jq8OTVLWvQrR6uexb2RrRkZGRI7I5Gzbtk36SI/7k5/8pFQRZ9mM//zP/wRQ05NktSjfr7zyijAvhC4w6hULaxbQy+fzjrW4vLwsa0YzqJQ77hPXrl0TdoA6Ut8FxbHgPjI5OSlsGeVbM+brcSAGqOlUvUcCjQU+yRhv27ZNwjiEDrOS6SBD9Oabb4os6MiC1jNAY7K4l+UzNEvPPZB3aiWTSdGTDL+Ojo5K8j3bGIvFZK/k+PMwyOHDh4Vp14VU2VedFL8WRtIyPhYWFhYWFhYbBk0fZ6eVnc1mxauixd7a2iosxZNPPgmg5t3Tq2aMuVAoCKtDlkDf0EsLkdaxLnJFzzubzXp6t4xOpAQaY/1MZNbHuhmP7uzsxOc+9zkA9Xjlnj17xFL/9a9/3TBG27dvF0ufz00mk/I5k1MTiYTn8WjzmGq5XHYcU69WqzIX9Kzy+bwjdyUWi8m/yQAwsTKZTAqzwPjuyMiIzLm+BXw1962sBno82R8yjj6fTxgELYf0ljWDSNaLY8d7ZO6//37H1Q3FYlG8PLcEbq88MD5bs0tmwvHY2JiwOvSeb9y4IbkvZDi2bNkihdG47nReD2WUpfZTqVSDBw80JsR7cWTfzLfz+Xwyh/QsW1pa5N9knpeWlkSOyF59/vOfl38zr4X9Gx4eFtnl8y9duiQyQV2Tz+cd+sHv93vCvurx4jvYlpaWFmETuRavX7/uyBHs7OwUFugf/uEfAEByLY8dOyYMLpnWxcVFeS8Zr2Qy6TkbYo5PuVyWNuucMDKnnItAICBMj765nKw4y07waPj58+dFP3Hu/H6/rGPKdblcXrerKrT8m1GPRCIhOZ5MOu/r6xNWh/mi09PT0ke2XR/IIFtCPTY4OCg6WJe2WC+mB6itdTN5+r777hO9SDn99re/LQd2uD4PHz4seoprl32JRCIyRlyfi4uLIgfcF3WBY2Ilh0Wa3km1EudEsHHJZFI6SXp58+bNMhhs3CuvvCICbVLH0WhUFiOhF4yubGkm+XkBtxMAmgImRUzldODAAaGhqaQuXLggCdpsN+nmvXv3ymRz/CYmJkQQ+P5QKNRgIPCnF33Vi1WfkgMaq5uy/5s2bZK6GhTAZDIpCZfcHGnELi0tCeXJcMv169cdl9XqU4Beg89NJBLSX85ZIpFwJNePj49LvRfO8TPPPCObJvvIMbl586b0Q9OxbnWJvA7FmgZstVqV9tFQi8fjIpfc8PL5vIQbH3/8cQC1iyv5NzQMqGw7OzvlYksaspVKRRS2Plxghke8MAq00tXVxtlGvp+ntuiIAfVKx3v37pU1SGOARoLWV1TIunou16TbhtnsOnRzJLlBc6wfeOABMQZo5E5NTYm+pR7x+/34+c9/DqC+idJpO3LkSMOFpUDNEObvuCaSyaTn1YzNvoZCIZkzylgoFBJHkMmtAwMDsj9wbU1OTsr80qk8ceKEfIenufRlrZxbzmepVHJs2l5W+uf/OVf8XSQSkTAj++j3+/Gzn/0MQL1eXU9Pj+hUyiPnulgsijxybnUSPnWWPg2sUxvWqmfNu9UWFxfFMOH+FQgERGb1paNsOwmP9vZ26at5gGFyclLmlc8vl8syDhprqTNlQ10WFhYWFhYWGwZrZnxMej0YDMrvGCJIp9NyZPTgwYMAah4omRBdV4HWKj/TVUPNo6v6rh5CU80mDb0WmFfd6zoEfPfCwoJ4z/qOMd7zwzoEOkGSFjx/7tq1S8JkfO7s7KzQo25H172udUOPIBAIiFdEi75QKIiXRYtejwXnSXv+5pHvK1euSNv5/EAgIHS0liWvQ1xmEqrP55N/U+b8fr+Dhezq6hLvmt7wsWPHJGGdbMHly5flO/RUzdoUgLOe0HpAh13pDZIq3759e0MJBaDmPZLxITW9fft2R4I7+9PT0yPPIxuxtLQk79Vrxq0cRLPQFVopJ2xHW1ubMAA8/v3KK68Ig0I9dOLECZk7hoHoRR47dkzGjchms66Jv8R6VTVeWFiQ8SSTs3PnTpFF6odisSjtZz2XmzdvCttKho765v7773eMU7FYFNnVjJfX9+WZ0HeeadnlWqTe6e/vF/aJa7a9vV3mlt/TdeH4DB064Xia87ke0OykuS8Fg0HRLZTfsbGxhho9QO02gM9//vMAIFWMKZ86dKfXGPvGtWKmLgDNyaqung407g884HPlyhWp88X+LS4uyh2OvPvu8uXLsr9RVzIVor29XRgf9kHLpN4n1rIvWsbHwsLCwsLCYsOg6RwfXXCLVhu9hmvXrolXwdyOpaWlhnguUGMIaOXS89DHHE3Pkz/1+wHv4rRu/dNMAX8GAgH5N+OQY2NjEo+m9ZpIJKQSNY/o0fvO5XLCpOhYJi3bO90/5jXzA9SPc+tcK1r0ZPIymYx4J8wT8Pl8wnTRGifzEwgEJDeG8xuLxURe1pMFIXR+lsn4LC8vS1vpoRw6dEhyYhiT7u7ulnwQFvkj47NlyxZhgyj/fr/fcReR14yWhr4DjGwbWbju7m5pF+XszTfflLXI5Obe3l7xtHRVaqDmqZKl5Xqen58XL5N9baZi+p3gVgWa/47FYsJa6Vuwzdutjx8/LgcM2E8maheLRQdbl8/nHX3R7LbX/aR3Wy6Xpb/6BnH+jjommUxKHgVZrcHBQckhYT/IfMzOzjYUhONnfC5z9nRJBK+hWVi+j3mcc3NzMi9kA/Q8cs3u3r27gXUE6uxmPB6XQqn8TrFYdE3y9XoeTT0dDAYbDvvwO1yDzKkaGRmReWY+7NatW0Uv8Si4vsfLPKauE40pR17Lp5lvF4lEZO707Qy8D47z8JnPfAZf+tKXGvo3NjYmpRrMki6JRELGi3BL/Hdr20rQtOHDBoRCIRkAbtrxeFwWGSdgcnJSJphCXygU5HMKOAWjUqnIotShA7OTXiX6mtCJxGbdlVKpJAuR1Gq5XJbJI525detWR60JGg75fF6+rxPSzPffLfB9NICCwaDMJ8c3l8s1VO4FGpOg+bdMLGxraxOlTEWka73oKzPWYw41AoGAIxS6uLjouNxPnyrg786cOSPJeDqBH6j1WfeNP82TMV5dT6FhjpmuS0SZmpqaEjnjKaCzZ8+KHHItHjx4UBQOFTY3FKCehMo+5vP5BkcEqM2nl8asW/+4Rhi2KxQKMq6ck2effVb6wv5NTU2JXLJ/NGxjsZg8T5/gMhOp19NQ1zqG46ovuTSvRdE1YWjc6FAOw5bcQFtaWhzt179bL2NHQ4e2uWaoY/RBFvb7nXfekT4xtD4wMCD6lb/jM3Tyuw4NcTw57/oCT6+h170+lQfUjDe2lc7F2NiYyCr1zvT0tDgk/EnHUVd61k7del2H49YvoLbvm7q9v79fDBqivb1d1hYPuly5csVxibnuk77mB6jJg1eFNxDlAAAgAElEQVR9saEuCwsLCwsLiw0DzwrD6BozmgYj00GLTt9BQ68qEAiIVUfPWx+x5r91YpOXtQnuBO1tml5RuVyWfjPBsKOjQ8I6tIR1RU0yYPS+/X6/eCVktLRl6+UljyuBSWXq8dc0POl1el2RSMThXevx0qyO+a71KENwJ5h0cD6fdxxZjsfj8m96y5rZ4BzrJG+3hF6TJbgbDJ7f73ccRdaMJUN4W7ZskTVFVicWizkuS+TfhcNhWbP6clCzLtF6z6P2Yjkn6XRa2sb2plIpWYNsb7lcFo9ae+BALQxklhrQ9ypxDps5DrxSaB3Htre2toqe4e96enpkDMjkXb16VZghfZkjUJtDM0HUjaFbz/5p+TAPrsRiMUetGL/f76h4r+vGcX50uQGzzEggEGiorwV4W8n4dtCHczQzZ9Zki8fjwnaxnIS++JahS13fzqxyXywWHWtvveZR7/GUJ+r91tZW0Y9s9/79+6UtTAFZXl4W9tWMKlSrVUdNN11NXP9uTe1f019ZWFhYWFhYWHwI4Rnjo++yolWmvQtCV5LkT50saFrCbt6jW9zybrAFZqKxzkmht6nvDKLlrpNCWUlUW+vmUWdddGo9k2Hd4Hbs2ixa5fP5xLqnBxoMBmXeTUu9UqnIv+lt6fj63WJ6TGiPT9/oDdT6w8/JfBSLRfE4yZCw7cFgsOHuL/68G4nbJnw+n+O9+kZzsnSlUkl+x3UaDAbFW+bcapkwmUj+Xn9vvedTrxk9/vr+O6A2/lxvujAg+2XqJrLNGrrIHdFsleaVwlz7mskjS6XvOdQJ2VyfZBn0LfZux6BNfXo39I7W427J/2xzW1ub9Juf53I5x3rT4HN1Uc17pW/MtahLFXBfCIfD0l+uv5s3b8q/me+i55V9dDuer8ssrGd/3RiXcDgs7WSfJicnhTlnEjRQ17eUU53HazJzOnJArDWHydM7EEzjRSd3apibq6awzIXgJtT3YqPU73QL1xDxeFwmXRsAJn37fjSrF7WImoFup1mGXVfPvFP7zL/Tz/2gQVc9JahQ3C4TNRfgB6lfbpeBuiXM61og+nNTNvWapDK6W6cM3aCVHWWrWq3KuiNKpZKjLo/P55Ows1mDJxAIOBK19fc+CKCc0Ugz+wfU2mueQNXz5aZ77raDRbjJqVslctNI1cnf5rN0mFDXsblX82hW5db7h9tFsG6GjDmffr9/RSfS7maf3cgLJtfzJ9B4G4G+cFtDH3hyO7ndLGyoy8LCwsLCwmLDwLcai9Dn800DGFu/5qwbtlar1dT7felD3D/go9/HFfUPsH38gMPK6W9g+/iBhu3jb/BR7N+qDB8LCwsLCwsLiw8zbKjLwsLCwsLCYsPAGj4WFhYWFhYWGwbW8LGwsLCwsLDYMLCGj4WFhYWFhcWGgTV8LCwsLCwsLDYMrOFjYWFhYWFhsWFgDR8LCwsLCwuLDYNVXVnR0tJS7ezsXK+2rBtu3bqFdDr9vrWu4/F4NZlM3o0meY4bN27MrKQY1Ud9DgEgFotV29ra1rtJnmNxcRG5XG5FfYzH4x/aPmaz2fftYyKR+FCuxfn5eWQymRXNYSKRqP5/9r40SK6zOvvpZaZ7umef1izad8myFsv7KtvYGDAGjFlCIIEQEiCVSkGqUkkqP1OkUpWkko9UUimoAkKKLaw2NjbY2Bh5t2VZ2Mj2aB3NjGZfNTM9Pb1Mfz9unqdP39uWZ7kjA7rnT0vdd+6973vOe95znnPec9jX77eJxsfHFzzG31adOjExsSA5BX73ZTWRSBTZK+y3iSYnJ9+Qh4syfJqbm/HXf/3X/rzVBaR/+qd/WtB1jY2N+NM//dNF3XuhzVJ5nbuB50L+diH093//9wuqrNnc3Iy/+qu/WtS9K73XQnqmuJu62n8vtrncv/zLvyz42vr6evz+7//+gq/n+7ipEm/d39n/L6RJ5/nG/O1vf3tB7wo4Y/zEJz6x4OvfiNx9yGxTw4X0Alosff3rX1/QdY2NjfizP/uzRd17qXJa6R5L7Qn0X//1Xwu+tqmpCZ/73OeW9JzlvqebFtP0+Ytf/OKC79vY2IhPf/rTS3qnN5O7N2qs+kZNSxcjx1/+8pcXfO1SZHW5ZPePN+v7+Ea0UFltaGjAJz/5ySU9w9L5+LMS9LWvfe0Nf/O1SelCyDYcs41I3Z1YSbFYTJ15eX2lRoJvNXERhkKhsn/z092MznaSZkdadurN5XK+KzY/qNJGeL4mgJa/5Bmb0tmmoEs1hlaSQqGQp1GsHR8btZKPmUwG09PT+jfg8LZSk8i3aoyVNgq+nx0jZZQ8Y1NF22zXNt11z89Kd4R+I6o0r2yYaH9jw0t+x3U3NjYmeSZ/bUPe3wQ6n1FaqeElx5ZOpwE480HecR6qqqoqNqZ9q5t6Wv3hdhhtp273eIDS/LCpaz6f1z0W4qCsNLnfwTYMpsxGo1FP82SOYWZmRjzlGGOxmEe23ypy86bSb5avHCffO5fLeWyCqqoqj/G0VCMqyPEJKKCAAgoooIAuGlpxxKeSdU2PhJ7x/Py8rFb+VltbC8CBEWkJ0wMlQgK8NZZtJSSHZL1ikkWo6EFyfLFYDCMjIwDK54pWv/3urfBQisWix8rO5XKYmZkBUOJFJpPRvBAF4W9zc3MaN/NSwuHweZGCleRrJWTK7TmEw2EPcheLxVBXVwfACVPwOgA4efIkzp49C6DE79raWiSTSf0tUPLm7H1XkiohkXyH2tpaySEpm80KuSKP+QlA4ycVCgVPGNc+a6XofHLCNRmPx6VXrH6pqakBUEKyKKczMzP6jfJaU1Oj63iPCwXVu8mikHZNci4oY0BJBsm7/v5+AA7/mONn0Ui3vrF8vRB6p9Kz+F04HPYgPlVVVZJd8op5Nvl8XjI8OTkJwEG+3AjuW0mV9kXyj5/xeFzyyD2CfOzt7cXU1BSAki5as2ZNmQwA5XO3UsR5tfyibHEt8v9Aad9Pp9N6N35HlGdmZkZjsUieb+/s+x0DCiiggAIKKKCAfkNpRRAfekZAyauixVcoFHDu3DkAQE9PDwBgcHBQHsfGjRsBANdffz0AYN++fRgaGgIAPP/88wCAEydO6P6MDcZiMf3bjcL4QZWSWK23RQ8rGo2WWa2Akz1PL4ueCN81k8nIc0mlUgAcz4X3mJiY0HV8hs2r8ZMsukMKhUKyyulhTE5O6r34W1tbG1paWgA4pz4ABwUBgNWrV2PTpk0AoGvi8ThGR0cBlPIQ8vn8BUEK3N5WLpcrQxGBcn4T5di8eTMuueQSAJAn9sILLwAAHn/8cRw+fBhAyWPbuXMnduzYAaA8D+FCeNI2F4LPJfrU1tYGwEl0pxzSozx9+jR+9atfAXDWJVC+xri2Of6Ghga4T3xYJLRSjN8P4hzavBY3MjkzM+NBiWtra5Ubcfr0aQClNbZ7925cddVVAICOjg4AjqyfOeOcG+DazeVyuu9KedNvtA44/1YHkD9EPGKxmN6ZOpZrrb+/X6gr12RbW5v0r0XtqLtXktx5SZFIxJPTOTc3J/7ZiACvI+LDddrR0SEeHzt2DAAwMDAgnnFu4/G40ASLxK4UWb1D/lFmY7GY1tG6desAOAgO35l65vXXXwcA/PSnP9X43/GOd+jvOAdEUObm5vTvleKnG0mOx+OSMfKmoaFB+z7fp7u7G729vQAgtPz48eMAnLHTFqAOtbnAnJdwOLwkXbNsbldKVLKGBzd1MqRQKKCrqwtASRkNDw/rem6MnIjt27drQru7uwEAjzzyiL7bsmULAIfpFBxOth9K125SnHSrfMhEUn19vb4jzBqPx8VEGjcvv/wyAOC+++7Te37qU58CAFx11VV6Lo2HoaGhsiRTYGWUrlsR5XI5GSZ2Q+EmumfPHgCOgcp3/sUvflF2/fDwsAzfffv2AXAUMQ0kbijFYlGL2e8N0xqrVIo2qZxGqjUu+c4bNmzQbzT+eB1leWJiwpNYWFNTI5mk4RuPx8tCgEB5WMEPCofDmkfyqa6uDqtWrSr7rrq6Wu9/6NAhAMArr7yiMdLI4wY5Pz+PX//61wBKa7GlpUXP4ljn5+dXNKxQKWnc8pWGTDqd1ntQeV5yySV4/PHHAQD33ntv2fW5XA7btm0DUDJ8stks3EeVZ2dnpX8ou36R1TduAz2TyWBsbAyAs5EDjjzxXcnXwcFB8YnfXXrppboXDVqGTaqrqyUbdt1RB/i9YVqj1a2zE4mEfqcx3t3d7Qk3tre36350OCi3+/btwxVXXAGgtD9MTU3hlVdeAQBtwIlEQuPmWP12vGwY3e4b7kTmRCKhObDf0aglH9evXw/AMdK57rhOd+/ered2dnYCcOR3JZ1JG9biu65atUr7OHXi5OSkAAwa4Q0NDdi7dy8AeBz9VCol3vG+k5OTkgnq3/r6ej1jMYndQagroIACCiiggAK6aGjZiI9FHSxsBziWH2E7QuODg4Oy+Hjdtm3bZO3Sonvqqad0X3o0hG07Oztl3fO+a9euPe8RuqWSRQpopdPLsx4lob1kMqm/oReRSqWEdBAh4b2+//3vC3Kn53L11Vd7ErrdyNJKUDgclrdhUTuOkXyLx+PiKz9TqRRee+01ACXr3ULwTMCjdzA7O4tTp04BKHlqiUSi7OgiP/3wWMiTfD6vubUIAd+Zz41Go/LQGDaIxWLilTsJ/0/+5E80d/TGY7GYEAR6bFNTU5Jxzqdfieucp+rqaq0LymV9fb2QO8LJBw8eFLJqE2R37doFwJFDoORRzs7O6jp6V/F4XOvYzqE74RkoTxhfDkWjUc01ZXNyclLzyfBGOp1WyPzAgQMaC3loxwUAe/fuFQr32GOPAXDWHVEBzmkymZTM8j38QkUqhdGJUPT29mrNUHZ37NiBNWvWACjp06mpKSHMV155JQDgmmuuAeDo35/85CcASrp2eHhY+tcmpbrLhvhdM8jKKRHR2tpa8ZGRgOPHj2uM+/fvB+Dw4KWXXgJQQsWPHDkCAPjRj36E97///QCcdQkAW7du1X2pv20Yv1JStR9k9w17EMStz3t6epTCQZlqb2/H2rVrAZTWG+uT3XjjjbqOaN6WLVvw9NNPAyjplr6+Ps0xoy5+hPXOt9fOzs4K3WEoq6enR/sbef2FL3xB+4c74X7t2rVCt+z7UhfbKIQ71O5O8K74/m96RUABBRRQQAEFFNDvCPma0eW2LDdv3izvkVZbOp2Wt0xLdc+ePYrt/exnPwMAHD16VL8xnkvrMpFIKO+CSMqmTZs8xdhsLHWpZI9w01Pgu05MTMhiZR5AsViUJ8JY+tVXX62/oTV64403AgBuuOEGxdqJkJw7d05eOZPaGhoa4C5vH41Gl+WduFGGaDTqyQ2pqqqSd0sPzCbK0rLnmIGS5898JhuHZV7P0aNHNUZbpMsda7fHIP0Yo30G5TQej3tyHEZGRoSGcDxzc3PyLpgTRM/jHe94B7Zv3w4AePbZZwE4c0O0kuMvFouaAz/I8t8mNLtzYEZHR3U44IknngDgyO/b3/52AMDll18OwMmnYP4OkRO+7+TkpNZTa2urnumWwVgs5skPcSeP+0VcnxZBZALoqlWrpGOIvJ09e1YyS71y7bXXAnDQEaJ1zFPr6uqSriGK0tjY6ElQ97v4ZjgcltwR8ZmZmdE88p3e9ra3SQc9+eSTABzkgzlNlAOiscePH9cY+e6Dg4P6N2U4Eol4DolYhGSxZOfHzhnlwx4EYXL9o48+CsDRI+Qf5W56elr5IW9729sAlA69vPjii9LVRLV2794t/WVlplJuj595aZFIxFPmIxwOS+dx/OfOnRNyxb2ktbVV+yD1ji2A++qrr5bdN5FI6B6UheHhYY8s1NbWLjsqYgsIUj+Qh9PT01pjvO748eNCKZmLdO7cOe1vX/3qVwGU9v0DBw549vNUKoWdO3fqfoCjV925UQsh3wwfm+TESZ2ZmZHyZFLeoUOHZBAQtmxvb/fU26CwZLNZbfiXXXYZAEdYuBAIx8diMfT19QEoKeqlnn6ygk/BzGQy2uSofBobG7UQmcx16NAhJYySEV1dXXjooYcAlBYiGXjllVcqXEJYOpfLSSD4uXbtWkHzvN4uqsVSpQrTNTU1Co3w5E+hUBBPCJ/mcjltAkwY7OvrkzFHWJ0Jdj09PVroNPJeffVVGU+EsWtraz38Xy6571NTUyODh4b6qlWrBClTsbzyyitSnhzrunXrtHgJ2zKBPRwOa0H/8pe/BODwnaeEyLvp6WmtBZss7+emGY1Gy6ryAo4RxhAPefGZz3wG//AP/wCgtDF+8Ytf1PrkeqJReO7cOSUcUn6B0nrgs5LJpMZDoxlYfEivUnVbwFmTHEOlkzJ8j0QioaRt6oTh4WEZ6VyzNIAaGxs1ZhobLS0tuh8N4UwmI2jeD75VquptjQ7r+Lkdvr1790rH8v1aW1u1GXCDoLF7+vRp3Y/yaqtTk9f5fF7vwDW53Ir5NozH+/KeXBN9fX0y0Jmg/e53v1s8YJhuZmZGBg+Nd85Jc3Oz5oQbqTW8qbPHxsbKKpDbd1wsuR0Am/ZhDxMAzvqjU0j9MTY2pr/nbyMjIzJk6IxwbabTaXz3u98tG/fHP/5xyTvXcyKRKDtlTVruwRhbf4djoOE5ODioMBUdj61bt2ptcR8HSuFJ7i20CXbt2iWZ4Nptbm7WWGkcTkxMePTEQuQ0CHUFFFBAAQUUUEAXDS0b8bFJo7T8bM0IWl/0oPr6+uQt0Xs+efKkjnfTQySqEY/HPSGHPXv24N3vfjeAkody8uRJj/W+1DCXhXRtNUpCivS6mpubhQbw2clk0uNJ9ff344EHHgBQSvb6+Mc/DsCxnIk8rF69GoBjMROOJjzLcQL+HL20NXtsHQR6J9aitr2MAMcqJ2pCK79QKChkQKucUOzQ0JCsfY5ncHBQKAivr6qqEq8pG8slN6RroVGOcevWreItE+hPnjwpr4X8jsVi8iA5bsrkkSNHND8PPvigxsj7ksexWEyyZZGS5fDSjRJUqsQ7OTmpuXjXu94FAPjHf/xH/e3DDz8MwKmVRQSOnhnX5PHjx4X0MDT2yiuvSFZtKNZdiXWp47IeuE2stsnvgMMj8pUec19fn1Aujj2bzYoX/HzxxRf1G8fCI/zNzc26L0NodlyVerEtdaxACSWuqqoS+kq+NjY2loUrAIdfRAWoI/bv3y9Uh2FXes0dHR248847AZRQ3Wg0KlmkbKbTaelPN1KzVHJ75oVCoSzhF3D0I/eK973vfQAceSVfmHReX1+v9fmVr3wFQGnfqa6u1r+5Jw0NDQlRt5WG3WNcKh9ZwoH8IbpTU1MjXtnkeFuzjX9PFNPWTSNqTuSEYzh27Jh0kV13nBObNExZ4POXQ+4yFaFQSCEu8m3Lli34yEc+AqCka37+85/j/vvv1/gBh+fULXfffTcACCFPJpP4/ve/D6C0Z+7cuVPzyzHZGk+L0TUB4hNQQAEFFFBAAV00tGzExxZlcic5TUxMeAowrVmzRl4N810mJibk6fN65lzk83mhQfR8du3apWQvegoTExNKIPYjkdKNhkQiEXlgtDbXrl0rK5qIxu7du3WUksmW//Ef/6H7ESGipzE8PKz5oMU8PT0ty5bWfHt7u+amUsfppVCleLZFJgBnfuk1kyd79+7V+zOWvHHjRs0Vva2f/vSnABx5YJIvkZzGxkYhPkQRZmdn9bdECpeTaFhpfkKhkKfn0tDQkL6j928TmckX21+MsWjOUyqVEpJJhCiZTMrbszls7t5Ky02mrORJ2zw7wMn/IG+Z4/D444+rbARzQK688krcdtttAEo8YB5XU1OT0CAid52dnbqOa3x+ft7XarFuNKS6ulpzR4+5trZWeX8WoaLne/PNNwNw1jGRG65PInUvv/yykjKJaN1yyy1CAamjbEFOv/oIuUtgVFdXl/Xz4zzwHYgETE1NSe6YY7dr1y6Njbzjve666y6V1KBc2zwJzt3U1JR4x3da7lq06Dm/o0zyu8bGRhUfJOITjUaFolJ/rF27Vmvqxz/+MYCS3rn99tu1Pom0z87OepKMLeLjV+VmGwHhc4mYk+bn58v635H4/tT5xWIRN9xwAwAokZtyuXfvXq0x6qlLL71USDzlJJ/PSz6W29HAouc2UZ1rgRGL66+/XhEN6obHH39cua9EKMfHx7WncQ9g3l2xWBR/OX/pdFrH2W2ephutXAgtmdvuRVAoFMQIJmDNzMwIoiPDQqGQ4EerqAmruysz9vT0SLnY8/q8B68fGxuTsPnR0sGtbKPRqBQ7N/H6+nolnVHQ7r77bmzduhVAqZ5LNBqVUHAeaDz97Gc/E+NoWESjUY3VVnz2C1YHKp9CyefznnYbXV1d2uQIQ1511VVSKEzybWlpKau7AQDPPfccAGfTYTiLCnl6erqsdQLgKGIqaPJ3uWN0J8bOzc15Wn8MDg5qw+Nis+Enyl8kElFdGHdp+Hg8rmeRT6+++mpZxXKgtMm633OpPH0jPjIxm5vb1NSUFD6Te7/3ve9JWZC3Bw4cEA+YSMpE0draWhnB5OOpU6cU2uVYc7mcb2057NiswW9PeAKO4qSCtFVjuclzHdkN3dZbIjFcxNNNV199teSFfM1ms762jbE8dFco5jsDjoFOQ4aHBFpbW6VjuYk899xzeOSRRwCUdDHbGlxxxRW6B5OHq6qqlLROwyKXy3nCP34fOLCnSDmfjY2N2uTJ29dee03vwhSHm2++WfyjY0xH6p577tFv3OxramrKmgcDji7ws+ab7V7A902n05612NnZ6al2Pjk5KT3DU1g2tEOjgfeIx+OaH7s/0jFhqLa7u7usXQvf0y8qFouSGb7HunXrZKBwn3jkkUe0b3LPnJ+fLxsPUJK/8fFxzQ0N+kwmIz3NOa2vry87Mb5QCkJdAQUUUEABBRTQRUO+HWfP5/Mea7e1tdXTM+X06dOy8jZv3gzA8cZowdECp0cTCoWEtPCaV199Vda7DcmsRPNOm1BJi5k0Njam0AifncvlPNVc16xZI6+MyA/rLDz99NOy8Al1Njc3KxxhG0u6E1bd/14MVapbUSgU5CERyXj99dfFV8Ku+/fvx3e+8x0AJX7V1dUJfWP4i+N6xzvegVtuuQVACRmLRCKeI6ShUMiDavkVBrKySV5Rxubm5oQS0OMfHh6Wp0R5veyyyyTHTLhjiOiKK64QjyknjY2N4invYT1pv5vpWpSAiB29oKamJiEi9JBff/11vOc97wEAfaZSKRw8eBBACekh+rZ9+3aN2yYc0kPneEZGRiQ/y+WjRUPs+Lj+OaaZmZmyysUcC+ef4aq+vj5PjZFbb70VQHkSPqm/v1+8s8dk/a74a9cgP/lvhvC7u7v1HUMDtbW1kmOurdHRUfGf645I5YkTJ/CDH/wAQClcdtlllynZljJvx+q3nNomoe7nETUESsjk0NCQUEUiV42NjUqW5dplIu1VV12FH/7whwDKmyhT99pyJ5x3W0tsOXx0oym5XE7yyPV08uRJ8YNh8YGBAeke6s1CoaB9gjqVYz1w4EBZSgk/iZIQTR8YGPAgPn6QPUhk+zoCTgkBjpVh5d27dyupnnP+0EMPST9xnVK/plIpRUc4TnuAxF5HpGkxPSwDxCeggAIKKKCAArpoaMmIjztRLRwOy2qnBbh9+3bF9YgGPP/887IMGUfv6OiQF0aEg/HL1atX6xn0RHt7e4Wm0PKbmJjw7WiivUele9GC7urqUsEoWq6rV69WfJmxzL179wr5YsydSEFVVZXyD5jrMjU1pXngd01NTZo3etOVClMthXif6upqWcv0Ik+fPq0ERFbhtt2cWUTsqquu8vTdoVdz8803y1K33ebPNw6/c0TsM4gcEgWoqqpSMiSTZfv7+/Wu5E9NTQ2eeeYZAFDxMOYx9fX1eaoVx2Ixxdwpw0NDQ+Kj3wmVVlbdCf4dHR16LnM7UqmU8tG4jjo7OzUvzDkjIrJ69Wr1AuKx2R07dgh9sD3I3Me9/SDbY41ID9GY+fl58Yle9OTkpFAQohz19fWS049+9KMASnl3X/7yl5WzRi86k8l4Dm1EIhFPuQu/yfKQa2dmZka5clyLExMTKpjJ/KuOjg68973vBVCqSk3E4PHHH9ec2UrU7rU4OzsrHczv/JbX+fn5sqrogLNOiBJYdJhFUTnfL730kvQs+UMd/PLLL6uUBg+k7NixQ3xnLmI2m9XYbFVlP8geoODzbAE/6k2+U0dHh3QFk/SfeeYZrTeic3/0R38EwMkR5R5CXb1p0ybJMlGQbDbr25gqISm2WCrXzJEjR6RjKUOf/vSnVWiS8hqJRBTZsBWpAUc38WAC5ZooElDSPxZxWsxa9LVlBSeGmwcVEFBKgn3qqafEbA6spaVFsCbrTlAIbrzxRilULo6hoSFNMmH4TCbji8HjJgtBU/HxPXp7e2XIULi///3vSyAJS+7fv1/CyUVK2PW2224TtMlr0um0IF/Ooa2T5FeNG/d82RLynN9CoSCIlGOcnZ3V+zHx7MYbb/RU3+b9qXTtv23zPl43PT3t+c4v4hhzuZzkiZ8dHR2e0yVzc3NacISPjxw5oqReVtTm9blcTqfYuCnv379f4VzOoW0PsFJULBYFr1Px24R5hgROnz4tpcGaGceOHZOxws2GyvTUqVOSaY5769at+o7KLhaL+TZGW8uHPJybm9M6IkTe29ur67hm0um0jDxuHBs3blT4h+EThjmy2aySMrlJ2XYrNA4ikUhZCxL7bssla8S6W+QkEgnxgjrj+PHjWovUu7feeqvGRkP9e9/7HgBnw/jkJz8JoKSvz50756lKb1MXVopyuZwMH2u88LnUN+3t7XKmqCNffvllhYGoD+mEnDx5Uv+m471p0yZtwuTj9PS01r1f8uoOgc7Pz0sf8l1uvfVWHeahXEYiEY8TcvToUR2C4X7BSustLS1KNwMwStEAACAASURBVODeumvXLl1HmbEJ136SnS8aK3ZfpH7gCdG2tjalhXB/XLNmjeSUPOH66+rqknNNndvf3y9Z515cKBSWdHI0CHUFFFBAAQUUUEAXDS0b8bFHHekF2SQqWnK0AHfs2CE0h4hPZ2enPGjCWYT7isWipwpsKpUq88yB8uO6ftXWAMob2tGLpueQTCaFeLCS74YNG2Sl08JvamoqSzwESonCN998s6xzhvKmpqbk2dlj04So/QoDuSkUCsl7sj2W+G/WywBKR4GJaNgaC/S2aLFnMhmFT3ivPXv2aH7Iy3PnzsnL9ZusR04Pgby1cK0NiRGGZbXUtrY2eYif+9znAJRQg3Q6jf/+7/8GUKqdUldXp5CEffZKhUdItlYQ10x1dbVQAoY/hoaG1BCSdVKi0ainsTB5/eKLL0o+bI0jrk/O58zMzIqM0dZI4TvZI9lEPLh2Vq9eLUSWcheJRPD4448DKCXP8hj0tddeq3XMBPBjx47Ji7b1l9yJlCuRqM655mcsFtM46AV3d3drrhlO37Rpk5Ce//zP/wRQkuU77rhDXrjtrcRwmq3EbkO2fpLtqUTUlYhTPp/Xu9hSIvTwiWBeeumlSsjmO3Nt5nI5JffywEFzc7PWAu+fyWQ8NYpYgXm5ZOWf+wVTO2677TaNh81wu7u7xT/un0NDQ0qXsH3IAEcmOBdEirLZrFBqyn0ul1uxY+z8JEJMfhSLRelFolePPvoovvGNbwAoIax/+Zd/qYrNLL/wv//7vwAc24BjZaQjlUppjduE6qUcagoQn4ACCiiggAIK6KIh33J87LFTm/BMD5px9/Xr18sjo8V69OhRWej0vIkKjY2NCRFhRctVq1bJg6E1mMvl9Fw/ER++v0UjaHXu2rVL3eFp1UciEXnD/NvTp08r2Y5eDK8JhUJCSIh2FYtFzxxZq9bmFSwH9XHnJxQKBXmU9MCi0agn+TgSiQjpsUUr6W1wjLTsLQLIgnJbt25VciVRu8nJSaFaK5XjE41GPYUJOzo65A3xs6qqSjLJMabTaSXw8wg3E2T7+vqEiFE+YrGYp29cVVWVL5XFLbmTmzOZjNYMcyLWrFmj3zmufD6vXBbm6axbt05rj8ndRFVs/yZ6lPF4XOPlvWyRQD+qjLsRzlwuJ6+d44zH40KB6IHW19erkBs9xLNnzwrpIUL5sY99DIDjid9+++0ASjxcvXq1kASitfPz82X97fwki2q50c9kMqlCdkSHjxw5IkTqwIEDAJz5or7hOO666y6NkaUIyN9EIqE1SoR5fHx8xXLRbHd26m/Ky7Zt2xQJ4FjD4bBQL8rm2rVrhfQwGZpRgs2bNyuCQD07NzenwqqUnampKcmKX8idrUoNOPJP5Js5c1u2bBHCymP309PTkkfy4uTJk0KGOJ4vfOELAByesegokdyamhqtVa4LW+XcT7KdDbhHUdZuuukmRTR43de//nXlbH3gAx8A4OwF1A9EMLnGOjo6JBO87w033FBW4Rtw+Mq9ajHyGiA+AQUUUEABBRTQRUO+dWcPh8PyGol+AKXjprT27IkT/jY+Pq74IJEcWuAvvPCCkAOiK9FoVJ4sLVtb/pwUDoeXHdck0jI9PS1rlBbumjVrdOSXv3V3dys/gNZ6f3+/fifKwffv6enRkXgiC+3t7bJo6enMzMwIPXAfm14uWU+aZQV4yqKhoUFxcuYzNTQ0yGumV2aP5dMD5RiqqqrkxXC+tmzZomdQNrq6uoSo2I7jfuSLWM+cHpgtv8B3IRpz9uxZyR2RrL6+Po2X3hnltaGhQblAlP8NGzaUlWDnuNzHgpeL3NkTa/ykvPG509PTGg89/s7OTiE39Br37t2rfCzmKnGM+/bt0/X0suPxuJAzK6sr4WXaXkv2GDDg8NTd7mRkZEQoMT8TiYTejfcgv8bGxjRWoidbt24V8nLkyBEADhrqZ/sYS9RX2WzW4/G2trZqbESH+/r6dDSaOSSTk5NCOj70oQ8BAD772c8CcDzrv/mbvwFQKh3yzne+U+O2+ZRcM5Qbv/KYbC4Y5Yl83Ldvn8b785//HADwP//zP5JZ8mLnzp3KByHSSCThqquuEprFU6Sjo6Pad7iGbR4TP8PhsC/H9m2xWcol9c78/LwQDu4RN910k8p/cH/Zu3evUEzq/m9+85sAHLn7i7/4CwClPnS/+tWvyoqyAo7MVCp8u1y5tcfPKTvU+3v27FGeIFG2UCikshjcT/r7+/Gtb30LQKl0AcswbN682dMKY/v27ZJP6rfp6WlPHvFCxuZbk9JsNqsJtglIFEAeZbO1GzigXC4noeCCpdI9deqUFjbrAPT09Eigafgkk0k9l+RHMpdtJmrreADO5FMwWW/h0KFDUihM7NqwYUMZdA6UQgVnzpzRomfSaTKZ1NzwuunpaQnCSkHQuVzO01emvb1d0DPHc+7cOc2t3dgZniP0SNkYHR0tC/XwO8oGN1pbudndkHW5xMXQ3NzsqU9ik7qZbEkj3r7z2NiYFAvlk/O0Z88ebaRUYKlUSvLBxZnJZCoqouWQuzGiTW7m+46MjGi8R48e1buzHgZh83g8LiVkDXzA2ZSoyJiMODk5qdABedbY2LgidW7sxsv35jt2dHSIZ0zYTqfTklmGvG677TY1ZnXf98yZM1qnNATtmLn5kucAysov+DFW3iObzerftj6W7SXH9+O72r5O3AToLNLY+/d//3dVPGZiaVNTk9Y9eWmTYv1agyTK5ujoqJ7HMNX111+v9cnyEMPDw+ItE14HBgZkfDN0S7175MgRGYaVnE/uPzU1NQrt2UTq5RDl3jqlfAfqllOnTokfdJY++MEPah+gzg+HwzLA3dWfu7u7PT3kXnvtNelS7h+bN2/2NfWDRB7W19dr3qnjzp49q7XCtTg/P68j/KRvfvOb+v2ee+4BADX47urqkpHPw0Lt7e3Sp5yPiYkJycti1l8Q6goooIACCiiggC4a8jXURUua3oYNa9HzbGhoEErDhOfa2lpPvx9Wd6ypqZFHQ8vu3LlzgvBp9TY0NPieaGjHF4lE9G6EETs7O+VFMNlwfn5elWyZ4LVx40Z5bbSEiRClUiklHtKrOXXqlEIptP6j0ag8ar+OJbotZHuU0yY8MxRFpKC/v1/HMOmxXXvttfLGeJSWHllra6u8R3o9NsxCTyGVSsm6t71z/BgjeVdbW6uwB+XQ9g1jKC6fz8sro+dx9uxZQdSUayamFwoFeTT0GicmJjReen35fN5zhNbvrtfxeFzIKdG6yclJvQt/q6urU3iEHmomk9E6I88ou62trZJfwttNTU0Vk9jdJSj8kFmOr7a2VmuF3mZDQ4NQYIaOOUag1LOqUCh4Kv1yvN3d3eI1k/dtOQ2bsEq94xcP+fc28ZdkEUI3ImWLKT722GMAyhES/sZK42fOnFFfto9//OMAnLARj/hTrq2+8fuoPuduenpaMlmpqCDnYt26dUICyMeDBw+qDAHTJHj0+/Dhw1pvRIMaGho0F5SZqqoqycdKjTGdTkveiBzW1dWJj0Qkz5w5o+rilMGuri71t6IuIuJx5swZoZ0s+tvf3y/9zfs2NzcLEXIjw0sh3p9rpqampgx9AZzq4Awn8lnXXnut5Jh7309+8hNFOYg+kveHDx+WTPAof0tLi5K3uSflcjnNzWLQugDxCSiggAIKKKCALhryDfEBSl46LetQKCTvktZ5Y2Oj4rm00BKJRFkvI6Bk7W/atEnXsbz3c889J7TAJiiuBOJDT6ClpUVWLi3y2tpajZkJW4VCQV4Jj26Hw2FPryrOW3t7u6xzWsmvv/66LFvOQ2tra9kRQsC/pFiLatE74JzPzs7KuiaC89prr4lPFqFhUjdj86SdO3fq3YmYdHV1yaKn52JRNYuK+NFzzR4/pkxy3skToBQvtzk7RLrGx8eFkNC7IcoxPj6u+Dvz1WwxNvIxHo+XFf30Y4ycW9t2g6gW83MKhYLkl0no4XBYPOB7rl27VvxwF7O0peiJjHV0dOhZzO2y7Uj8ILeMh0IheflEV6PRqNalLYjJeaUMDwwMCH2m122PPDNHgt+l02nNgy3U6Eaw/JJTi1ByDjn/IyMjGjcLxIXDYaFwXFtVVVVleR9AqcjfO9/5TiXDcu6OHDki3UOErq6uTjrA5mv5MUY+Y3Z21qPbH330UY2RuVRXXnmlUHEijaFQSPsI872on44ePaoxWhSW6A5loVAolJVe4Tv6gcByrHNzc4oK8EBIXV2dZ6+89957hdwwr+fyyy8X2kEZ4HquqqrS/PD+qVRKY2QuqW0fQz4u59CPOxcqFouJn9yTjx49quP3PBCzdu1aT9mNW265Re1zOOdsnfPiiy8qYsK1aBF38rC1tdVTWmIhY/Mta62qqkqKj9BeOBwWAwgdx+NxKSibsU5oki9NODKVSmlCCWWePHnSUyXaVlNdzAS8GRFGa25uliLiBrN+/XolpDE5q7e3V0YBkwjn5uYEXXODYbgsHo9rQRACfPrpp/XuvH8oFPKEEpdL7g2lurpaAk2jYG5uThumrXvDzZPv19jYqJ4xHCMNv6uvvlobCjebRCKhRUpYPpVKab79DgPZBpfcqAmDT0xMSPFTiQDlmzvgyAANXG4krJeSzWYl17aPDIlyWlVVVeYY2LEul2wyLMOONMLi8bjCIzRWz5w5I0XD8c/OzirMytAJFdDll18uCJ/rOhwOe4wc2/zRz3FxTdjGoVSATU1N2hR5omRkZEQ8pHI8duyY/oZ1VSjzXV1dSuym/qmUGJrNZss2kZWgSCSizZHyNDo6Kr5Sdk+cOCGjgYbZmjVr9N6UZyY5HzhwQLLIAyePPfaYrqPBZE/luQ31pRLl3B6CoT5gcvUzzzyjdUSHpL29XaE4hm4zmYyMAsoadeqOHTuUNEw9VSgUyhqHAs7cuHtr+R12jkQinsTxzs5OrUXqE1sBmXOSTCblTFJ/cs/M5/Pah7gWa2pqJDN2/XF9cg0sZ22657BYLHpO/zU3N8tBJAjw9re/Xc/n+CYmJiTP1DX33nsvAIfPTH/hvnf48GGFRq1j7H6nhVAQ6goooIACCiiggC4aWjbiY+tZ0BskLGfhSMJV09PTQkToLbe0tMgzo9VOFGB2dlYeDb2SmpoaeS1EI2Kx2Ir0B+I9E4mExspntre3KzmLHlI4HMZDDz0EAPpsaWlRfxx6ILT+BwYGhB4Q+ZmdnZUlbMe5UrVDbMVtehF2rPzd9mShFU7PM5vNejq2s/zA6tWr5fVQDqy3x7+rra3VM/wienL0CqanpyWfHGt1dbVCV5Sxnp4ejY2yuWvXLk94hMjA3Nychy/xeFxekB2X394lyR6lJfpK77murk7PI3L64IMP4vnnnwdQ8hqrq6sFoRM14LvPzc3p3/zMZDIKBVk58sO7fKPxWUSJfLMVsamHdu7cqWP6XG/ZbFZjJXpgazi5+TU3N6exuOuFrARRNuLxeEXk2t3HKpfLCU3n+BsbG4WSUz4p852dneI/SzIQ5bLXV1dX+57w666s39HRoX/biunu3mhTU1NCAqgPr7nmGoWx+LcWTaZ8EC3L5XKaA85TKBRaVO2XxRDvV1dXJ4SV89zb26uQFZH1LVu2lJUSAJwDPtwb+J5EcHfs2CGE01ZJ5xhtPzTKsh9rkffgWsjn89LfFrHivk9+WSSd63NwcFC1sfhJnXzXXXdpLTIp3Mopn1lTU7OkPSNAfAIKKKCAAgoooIuGlo340BK1Ha5p0Q0NDckzoRU/Pj6u2C3/tr6+XnkX7hjl1NSU7mctehKfaSv8+tmF1np3tKLp4Q4PDyuhjpZqT0+P/oYF/W677TYlcdFqffjhh3U9vXLOQUdHhzwvWvhVVVW+e2Buyufznjwmy1d6kf39/ZoL8sIWj2TiJXluc7h4XUdHh3htc4jc/d78IspTLpcTSkDauHGjxvPEE08AcPhC5IMexc6dOyWL9BptFWB6N7ymvr7+vPkRfhcw5DPy+bxQDI6hv79f646VqB999FHxiMmj73rXuySblAHK5fz8vDxKenxzc3P6ty1B4CfS4x5nsVgUgsh8nf7+fq0tvm8qldL7kjft7e3ylIn4kL+7d+/WfNmEZ+owro3lJvmej2ySLd+L78v3AUp6JJFIeIp99vX1ide8nuj6qlWrhCjYInTuwqFVVVUrhmxRn1RXV5cdbAAcBJllToi4vvrqqyoXQr7X1tZKpzC5m3kwdXV1HqSrUCgIUSEa6kdl/zci8iIcDitHkDQ3N6fCfUQuEomE1iwjHGfOnBE/iFwyJ6impsaTU2vXnD3UsRJj5FqYn5/3lJZpbGzUe1M3PPPMM9Lz5GEikRAadtNNNwEoVR9vbW3VIQQmNFdXV2v/sMnVS5FT35Kbw+GwhM2GfThIJmmNjo56EiT3798vZcVBMIkpn8976knY8/orFTYg2QRUKgw+f3BwUBAeF+Hg4KA2ViZPvu997xO0ycVphZGnGLjRxGIxzSEV0koaPe6sf6AUIhkbG9PYmPRqK9fyPevq6qSwuJh5PVBanHxGXV2dxmYTSFcKcrYhL8qkrZnC0CLDdMePH/cYSC+//LKnSig3VGu0cU5ssjhpJQwCN83Pz5fVYQIcY53KliGOmZkZKVKGS2xdGIb4yO+zZ896jAD7LGsYrDRxXHyfbDYrOaWyffXVV6VruMZqa2v1b+oVyqtt5GrDTLadwUpTpZN+dqzkDd+ltbVVeoNGYE9Pj4xbvjsrV9sDJ3ZNuJvJXohwXjgc9pxIjMViZS06eD3XIk9OTk1N6eQrQ3fkdTab1f5h29K4Q5W5XG7FZdU2rbb1vah7mNRrT4BSjrdu3ao2DzxgwPe1DjPXZyaTuSD6BSg/6cc5th0ZqNvZTqS9vV3rzVYapzPtNkp7e3tltNqTvu5w6VLlNAh1BRRQQAEFFFBAFw352oSFlpmFMmnd04rNZrNCd2jRT09P63f3sfaqqqqKIawL4VUClRu72eqVtmYI4IyFf0MP48UXX1TiMi1cztGqVavkCVSyYv2q2bNQcodmbDVn2xCSRCs/n88LVqe3ZZPO6J3YZHE3WhcOh1ccuZufn5eHYo9H29Aq4Hig7qa70Wi0LBQBlJAEm9xciWd+HQleCNkjpjY8RH4QpWpqavLUKjpx4oRQSfKR97JHgi1C4GfNnvORrZxMVI1j2bJlixBH8m316tVCoS3PyWMmTVLnpNNp3W+lw8pvRHaNu9e7bVRsdSHHSFQkkUhg//79AEq8szqXesb2WaxUMXqlyCLMtjcZ4OhRhumIGNs+W0RPampqJINuBM+idNRJgPco9kquxUp7la2z5U7fmJ2d9VQgXrNmjf7NcJ7tHUk5tlXEl1LTZjlkZdTWfeK/7cEVEktnDAwMSMfwespyPB73rEHbQHa5+jRAfAIKKKCAAgoooIuGfEV83B6K9RBJ9lgtrdeJiYmy47FACUmIRCIV83jcFt+FQoAs5XI5vSffu7GxUYgIrVzGOQF4jv7apGV3ZWZ73YVAeyzxXez72Vwr8tXmdbiLvdFLsxWCK6E7FyJ3wpK7g3I+n5fXxPeMRqOeMc7Pz3u8ZZujYLu9A5W99wuF3Lk9+Pn5eSFXzOeJxWJCR4hE2sRhXk8Zz2azHi8sFAr53r37zcg+0+bCuYufZjKZikgG8whsdV3+v9Lx5kr8Wml9Y59ZCT2wx+35/uRTQ0ODxkt55XzNzc15ivYVCoULrl/s8/kOgIO4uo9Mp9Ppso7qgDNWdxFJd/FTew+7j1zosbr1XDwe9xzjtyimRUuIRjKZ3R6wcSepV5LZlUzgtu9vn2kr8HOctoivzQmyh2j4t+772R6E7t+WSr5qLFtn442opqbGI4CZTEYCSrKMcyuZt8LIsc/lRmgVBiE9a9iR0um05oafFPJ4PP6WKJ1KVGleI5FIWZNEfro3nkqbvDuk5L7v+Z57IahSI0ieMrFEfheLxbIaIPyOdD6D50KTG86vrq6WQc7PUCgkPthEbrcBZ5X0SkPnCyV3tdhKlM1mJYPWOHOPwW6glYzwt0o+3c+vrq72hDCBcieFn+c79MEN09JbJafuxpk2ZG6vqVSLxr3x25NUpJU46btUqpTCQIrFYjLYrbHOFAo6zJXChHZsb+U43Z0TgBK/CoWCxy6wdc7c665SmoD792W967L+OqCAAgoooIACCui3iEKLsfRDodAwgDNveuFvHm0oFour3uyi3+LxAb/7Y1zQ+IBgjL/hFMjp/1Ewxt9oCsb4f/S7OL5FGT4BBRRQQAEFFFBAv80UhLoCCiiggAIKKKCLhgLDJ6CAAgoooIACumgoMHwCCiiggAIKKKCLhgLDJ6CAAgoooIACumgoMHwCCiiggAIKKKCLhgLDJ6CAAgoooIACumgoMHwCCiiggAIKKKCLhhbVsiKRSBTZHfe3iSYnJ5FOp9+0xnUymSyyi/FvG509e3ZkIcWokslkkR2Bf5toYmICMzMzC6pT/tvKx/Hx8QWPsaamplipvcZvOp07dw6zs7NvOsZEIvFbO76F6Brgd1+fAs5abG5uXulX8p3GxsaCtfh/9Ls4vkUZPg0NDfjEJz6x7BdaSNHESj2Qzkfnu+brX//6gt6rqakJf/7nf76ga9200Pe1PciAyg0I3fd7s3sCwN/93d8tqLJmY2MjPvOZzyzk0vPScgtfLrbXype+9KUFX9vU1ITPfe5zi30lDy3kHd3NSpdDX/ziFxd8bX19PT7ykY8s6TmVmv2er4FjJdleiIxXou985zsLesf6+vpF6xr3uxWLxfM2GHX3AvKjmOtCdQ3g6NNPfvKTy37m+XoaVdIjy226+rWvfW3B1zY3N+Pzn//8gq+39GaNYt2/uXXrcuj//b//t+Br6+vr8bGPfWzZz6wkl+5xn4/Xi6VvfvObC7puOeNb7Psudt8/H51vfCveVrmSwFbqHM0GZvY7wGm4524+Fw6HPR3N3ypyj69SwzjLQI6PHaKBUsdhd3fz31QqFouaf8svNg3kONiAznaQZjPaWCymxoO811vZDNKtPO278P0ikYiasnIcttO7uxN2oVDwNA18Kyulu+fXNgC2DR/ZENHdVDCVSoFooZVj95p9q6jS+Ei2STB5xzGTX/F4XB3pOfa5uTmPfL6R8XAhyXbC5nvZBp5Wf/I6wFl3HC91UCaTWbSjtZLkbnZZqSGnbZjr1kWzs7Nap3btkt6qLu3no6qqKvHKriPqTfKK3doBSFapd0Kh0IIckwtBHMP5jNFoNFpRdvl/rkFeE4lEPLKx1HEGOT4BBRRQQAEFFNBFQ74iPpUs6Hw+X/abRXempqb0ye94Ha3fpqYmMA5OZATwWnrz8/O+woALoWKx6LFU5+bm9J2FLulFc8y0iBsaGpBMJgGUey7uMfgJAS6G7LMs8sb357is10hvi1Z5JBLBwMAAAGB6ehqAA4GTr/RYrPd6oT0Wt+xYT5+y2NDQoHETNbCoCK8j0pXNZj1y7f73SpHbQ64kq/ZdyJfR0VGMjIwAKCEibW1tAIBVq1ZJVsnbfD6vf/N667Gu1FgryUklVIDvxM90Ou1Bsjo6OgA44+R1vCafz3uQW/L5QpNddySLKlK3zMzMSHZbWloAAJs2bQLgrDuiCMPDwwCcuaFsvFUoiEUEKiHB3Ec41lwu55E76qL5+XnU1tYCKNctHKP7E7iwaxIojZdjtWuL7zw6OoqJiQkAJV51dXXpXuQt8xkTiYTmzI2GrSQtJJwcjUY1ViJVtbW14it5ePbsWQBOfg7RLe47NTU1HpSrWCwuKeoTID4BBRRQQAEFFNBFQ74iPpWSBGlxWi+LHiU/JycnZfHRW06lUrqelvCVV14JAKirq0N3dzcACEmYmZlZUau9WCxWzGHgmDk+mzdB6zSXy6G/vx9AaXz8ra2tTR41PZahoSH9m5ZtLBYri3WuFFmUhv/nO9BiT6fT6OvrAwB0dnYCAPr6+rBjxw4ATjIcUIpHd3d346mnniq77/bt2zUeei7V1dUXxPN0IwPZbFbvylj65OSk5G7t2rUAHK+rp6cHAMRP67Hxnem15PN5oV9EK+PxuCcnYaXGZ/9tZZceVCKREL/53SuvvIJXX30VQGkN7t+/H4DDM7470YXW1lb9m0jCzMzMiuf78L0tumrRAL4H19Hp06cBOKd1iPBcf/31AIB9+/YBcFA8yvOJEycAOPwiesC1a9GDC0FWXjhGyuvMzAyGhoYAlNbixMQE1q1bBwBYs2YNgNKcbNy4Uf/m342MjOi+HGMymfQgLytJdr1TN1r0342cVkLRT506BcCRDY5j9erVAJz1R9SE4w6FQhckr9Ktt+1zV61yDuKmUinpTfJndnZW+9vk5CSAEt/r6+s1J6+99hoAB5HmmrXILHXQSqPoNp+H/+Z7tLS0SM/bd+R4yEPqoWPHjmFsbAxAaV+cnZ3V9ZSRRCJRhuotlJZt+JwP5rLJS5z8qakpD3NWrVqF7du3AygpNDLzhRdewLlz5wBA17S1taG9vR0ABAVOTk6uSKKzHZ/7JJaFni18x8XG7wYGBrRRctFdddVVAIC9e/dK0BluGBkZkaBTEGpra5VYakNJfgizvQcVBp9hQ40UuhdeeAGPP/44AODXv/41AIc369evB+DA6QBkHE1MTEjorTHE+eRvyWTSE0ri3CyXrMLkpkXFMTIyokVGam9vx9VXXw0A+jx9+rSMdfKWvF6zZo1gW2s88Vk0fCKRyAUJ/7jlIh6P6zuunQ0bNojfJ0+eBAC8/vrr2LhxIwDgsssuA1Aa/8DAgAwC8mXTpk0yDCoZWX5SpYRzG+5wJ5wnEgn9m+GA7u5uD++4Jn/+85/jxRdfBABs2bIFQMmIB0pr0T53JRNlLZxP4hgr6SXqlG3btmHnzp1lv1GfzM3NaRwc2+joqHQsKZlMrpicnu++0WhUGx3Xk3UW7MZHWkku+gAAIABJREFUg5xr7JlnngHgyDB1EfeM0dFROS29vb26B3WVO93AL7L6xiac8znUFcPDw3jllVcAAC+99BIAh2fUwxzHu9/9bgDOuqMxT5mNx+MYHx8HUJqncDisebQ6yE9yh535PKC0ZpLJJOrq6gCUwnUvvfSS3oV7G/82mUzinnvuKXvvo0eP4vnnnwdQ2vebmpp0X/LQrtM3oiDUFVBAAQUUUEABXTTkW6jLog/0MuLxuKwwehezs7M4c8YpOdPa2goAuOWWW3DLLbcAKHnhPIPf1dUlC/HZZ58F4Hg9fIZNMqX36iedL3xXLBY1Plrme/fuVciHdPjwYaFcHDM9ynw+LwuVHujU1JRgWSIMLS0tsnz5LPd7LZVsAhrHS361tbXpuUSk+vv75fG/613vAgB8+MMfVsiO1/FedXV18kDp4fzoRz8SUkDEx6ImRIvy+byvnmehUNAz6FnyE4DQjjvvvBM33HBD2Tgee+wxec579uwB4HjXgOPFURaI7r300kuCcEk2MdYmA/vJR97TPiOXy4k/W7duBeDMO71GesHZbFZIz7XXXlt2/1OnTuHnP/952X3vvPNOed72eLg7WdweP14uVVVVla0BPtudcL5t2zatM4bhUqmU3pcyefjwYQBOAUmO+e1vfzsAR144RzaE7Z5fyqlf4YRIJCLEx6JLvL8tgcHriHK0trZqLl5//XUAENoxNTUlOSAK1tjYKFSC8hqJRCrKkB9kZcKdKhAKhbSOuNYsOky0rqGhQTJw+eWXA4AQk+PHj2su3va2twFwwoDPPfccAGBwcBCAg6Jwz+BnKBTyNXJgyyfYJHmOjTwYGxvT+5MHl156qdBW7hHcP6anp7XGqItmZ2elS4nEZ7NZISIrsT9aogxNTEyUlWsBHHSZevEnP/kJAEfn3HzzzQBKBwy4FqPRqELQV1xxBQDggQcekC3AfdEi6ItBsgLEJ6CAAgoooIACumhoSYjPm1VypeVl43q0Bo8fPy4vhJb1+Pi4LD1a/sePHwfg5LbQ+6Ll3N/fLy+HselKCZ024XGx5K7Ia71yfuZyOc/xwa6uLnnP/G54eFgxV6Ic9DoGBwf1rHe+850AnBwMjvVXv/oVAGdO6eURNXijyrRLJett0Zuqrq7WuzDRrq2tDX/7t38LoOQ1Dw4OKlfil7/8JQAnFwgA1q1bhzvuuANAKV+kq6tLPLZH++kpcIx+FYurhIZwjMlkEu7WAel0GocOHQIA/OIXvwAAHDlyRAjChg0bAJQ8lMOHD+OSSy4BUEqabWhokPdGT6yurk4yzrFms9llJcu65TKfz8ujtGgW+UjKZrM6JMDcgJqaGr0fcw347lu2bJGMclxNTU2aT6KEc3Nznnw497MXSjZfiWuttrZWqAXRu2w2K4+SqMC2bduU5Pvkk0/qOq4jzvnBgwcBOOv5xhtvBFDi4cTEhGd+p6enPfqhWCyW5TYsl0KhkOTTHirgHBDBCoVC0i2U1+PHj+tvib5S72zdurVMJgAHCSBqYPUvZcgWt1wqovVGuphzxnHV1NTouaOjowAcpJHIiM3HIhJAfvP+ExMTQjyIHPf29krWORfNzc2SWVvo0E99UywWJftcMw0NDYoKMLeltrZWuXdEZKuqqhTlYASAuvXUqVPKS7zrrrsAOKg7USOOcXp6WvND1MjPApzFYtFTXPH06dOaz127dgFwDojwgAuvf//7369OCRwf1+LTTz+t9yXyPjo6qqjI5s2bNb6lrLslGT6VSolb6JmT3tTUpJfnRt/X16fsey7e3t5eT2ISs93vuOMOJe2RqS+88IIUD6G/SjUZLJS6GLK1AWyVaTKMiiMajWpxcixHjx71nCiwBgqZxI32zJkzOHr0KIBSvZR77rkHu3fvBlCat2Kx6Ena8tvwKRQKEl4Lc3PhUuls3rxZ333lK18B4Agu34ULjTwcGBjQdVz86XRahhRPnkxMTOi+nM/lhkfchnkkEtE8WgOdSpFKvqurS0Y73+H666+XUuJJrwcffBCAA8Py3amQ0+m0B0pvaGjQHHOM+Xx+SXLq/ht7GoTzTEjY1qOhHOdyOW14lL3e3l4cO3YMQOl0Gudp69atMvzI60wmI4OD/LTjJS1WTq3Bw7+ls5NIJKQvuO6HhoaUeM35379/v5IheeKpqalJxhCNVm4u27dvF+ROHfXaa6+JT7aOFb9zh7qWuh7dFWkTiYQMHj5rfHxcISvypKGhQafwaKju379fybAM3TIkG4vFdD3TCS655BI9i/rpzJkzeq4NsS8lMbbSqSbAWVeUE87tunXrpF85Fxs3bpSjQV4dOnRI78r7UY9s3LhRcs1rzp49K97yt61bt0qOuCb9CudRLjOZTFlNKMDZH1lXifLS3d0t3UKePfzww7j33nsBOCkUQCl019jYKMeSe8n09LTWIucklUrpd3focrFkDSZ+zs3Nae5oZBcKBe3LNPDm5+eli7gvrFmzRvsnwRDy45JLLpEO++53vwvAkR8aQZTnsbGxspPdHN+brcMg1BVQQAEFFFBAAV00tOzkZlqW1dXV8pBpYUajUVn0tPLe9ra3CcGhlbdx40ZZ/IS8COOFw2F50jzCNjIyIujTeki8jvdaqvf1RlCguz9IKBTScUha2iMjI0rYeu973wvAseYZLqHnwrAIUEpE49h7enqEoPGzUChUPDq7nGRK9xiz2WwZCgc43gm/o8fW29sr653JZs3NzbjzzjsBANdddx2AUi2Uf/7nfy4LJwCOd8C/JTJ27tw5eUe2bsdy4HX3v0OhkOfIfigUkszQe9i4caNgWobn4vG4ZJzeCD2U3bt3KwxExGtwcNBTjbWmpkbhWcrrUsfHuXHzMZ/Pe0JL69atkxdGD37btm2ecMF9992n8CrDX4Tjx8fHxRdbXZZJoxzX1q1bPfWgFguvEz2xyaY2iZHeK1Gpl156SaFT8mtsbAxHjhwBUPLA77zzTsHkjz32GIASavyhD31IcvDjH/8YgAO5M+xFeamtrS1DfflOy1mLblQkn89rrTD0c+zYMXnVPNacSqXECx4Qufbaa8V/6hRbG4frjijn+vXrdeCE8j8+Pi4d606yXiyRj+7DL3bOGCVobGzUXsF3Xrdund6B/KytrVWY3UYYAKcu0zXXXAOghPTl83lceumlAIDbb78dgBNK4j5jE+OXg6K7e1OFQiHxjM8oFAoqH8GyLQMDA2UVxwFH9qiDPv3pTwMA3vOe9wBwwu/ULUzkfvLJJ7UW+duWLVuWjfTYsbn3oGg06gmlRaNRoaqchxdffFF7CnXnoUOHpGtIRLRSqZT2na9+9at6fzevbZXyxchngPgEFFBAAQUUUEAXDS0b8bFxb1pjlbpT88hhKpXS8VB6nqlUSv8mCkRL+OjRo7qe383PzyvHgpbtxMTEspEeS5WqJLu7b69atUroFuO3zc3NuPXWWwGU4pDPPfecEBIiREQdbHIoLeHjx497ugrb5Em/ewXxvplMRqiarX5LlINH8gcGBjQX9Kx27dqlPBG+HxMHW1paFMslegCU5sLmMHBuK3W2Xwq5c3zC4bA8FHoNNTU1ig/znS655BIhA/RUuru7NW56YvSyr7rqKn3HnK2hoSEPMmk71fuVn+VGIsPhsNYFebJnzx49j96m7YfDJNDDhw8rB+jAgQMASqUXLOLAecrn85Jbzo09Yu1nJW5btZj/JmrR3d2tuebn2bNn9TtzAy6//HKhIKTPfe5zABykhHkvzCtYu3atECHS2NiYZHy5XaJJlZKliaAR8ZmdnVXOBNGLQqEgj5+fPT09+MEPfgCglCPIddre3q5nED244oorhPSQ94lEQuvXHvVeKlXKc7TE7yzqy3ymsbGxsmPcgLNmiVIxj4sIc6FQUI4WeT0zMyMkkLlAc3NzQuptArcfZKvC29wXfrqTlW3vQvI9FospF4hzwpzCI0eOSAZ5r8cee0xrkVGVxsZGz9Hy5dD59GmlKurMO0un00repm7q7OzUGLhncu12dHQIcabMDw4Oetb94OCg5ncxPFyy4eOGlWwohi/c29srZjJZd3Z2VmEfGgMWrqIgEKIsFouaWCZd3nbbbTJ8yIBMJuNr+fFKsJk72W/NmjUK05ARc3NzEsQHHngAgCOsNOg4FiYY9vX1eRJGz549WxbiAhxjy12m368KnLayqDvJsrGxUYLH68bHx5UoyPd8+umndT8mVtJQ2rZtmwwEKuzXXnvNU99idnbWU65+ueSu8WBLuNukTVvFGXD4yM2DFWFzuZxOGNKgoLEfiURkPNBQt5VhKTvT09NaoFaJ+DFe2/iQ46Vstbe3SwZZdbunp8dzAjEej+Ozn/0sgFISKNfdgw8+KMXETXZoaEinvjjWuro6rUUq3eUcNODcUP7m5uY89V9aW1s99UoefvhhGfKszzMxMYEf/vCHAEqKknN16tQp6R+GUT70oQ9J1hlmsY1ZreHjp3FnDxrQeMnlcjJGaFwfPXpUzgIr+D7xxBMyCqh3uRZjsZhOWHKM4+PjuO+++wCUV791hyuXS+6Ti5lMxtPYtlAoyAjjprljxw5tmtS3bW1tMoy4Zm01X1u5GHDkn/JpnRB3eGm5fLRNgfl/bu78bG1t1bjJl40bN+Kmm24CUJKzaDSqsX3xi18EUJLZWCymEKw9hEBnmwnS8/PzvrZXcQMCkUhE643GazQa1X7IMd9www3as8lf6iGglNpy//33A3D2HSZ0c13X19drrLa2Fp+xmHEGoa6AAgoooIACCuiioWWHuqylznAGrb3jx4+XQVf87Vvf+haAUs+g973vfbLW6YUzQXb9+vWCLZkYvGrVqrIEUr4HEQTeYznkrjwbCoU8FmV9fb2naeOxY8c8ntLJkyf1t4TlCGfW1dXJsmUIor+/39P3JBqNejyv5ST+Wq+GHqP1ZIlkbN682YNSJRIJvRc9zx/96EeesA5h2uuuu07PYDIt58E+33ryFjZdTnKzOxkvEol4GnPW1NTI46DsTExMyGvmu6xfv97Tw4kIQTwel/zRs9yzZ488aHuk1d1vyW/EJxwOC5Hi59TUlJLouT6z2azWLGXwuuuu8/RAYmJ6PB7HbbfdVjbGRCIhXlJOampqPPV7/OChXX/8N5GlTZs2lSVhA846okxy/h999FHJLJFMvuOzzz6rv/385z8PwAkH8diwTRjnc1eq8aP11G2Im3qSqMCpU6fEL3rG1113nZJEmWLAv5uZmSmrsA04c8N54vhthXO/e3bZcblRX9t8lO8ci8XK+pCRiAgxdMW1afvSUY/V1NRo3Laauq2J5ge5IwW2LpBFRvlcHmHfvHlzWcgfcNA36lyb8gA4oXb+Lfm4f/9+VTvm/bu6uoS6Urct59CPm2pqaiR3lBdbuZl6cvPmzUpaJ89tAjP3eCKPl112mfZ7IkWHDh2S7iLK1Nra6ql3tZA1GSA+AQUUUEABBRTQRUNLrtzsTsazLeOZN/D666/LWmO+y4kTJ+Rd2+RJ3ocJohY1odXIeCeteKA8MXe5Fq17jPY9crmcPBE+x+YVMW555swZ9TpiQqFFo3g9x9LY2OhJDkun054iezbXYSHdZxdDFgHh3NKKb2pqUiydx4W3b99elqTMcdHjYqya97rvvvvKkhI5VjeCZosV+tEvx8qBTSy0uSJ8JyJw/K25uRmf/OQnAZTiz7YTMHPQiB5s2bJF46cHGo1GVfSRcprL5Tzdmv0cJ+B4PswdoLydPXtWPGCeUjKZlPfL8WzatEmFQvkdZfe9732vkCGOZ2BgQKgW+R0Ohz3Vgf0kojdASZ727dun77kW161bJ2+Q3z3xxBP6G3fPrqNHj+IP//APAQB33303AAeFJY8pL/F43FOg0a88ikrJ4LZDvLu/3NatW5WkTF3b3Nwsb5lr9l//9V8BOLqZCBb1U2trq9AIW7LC5mfZ3/yibDbr6QN26aWXevT93NyckH3ybsuWLVqLTHy2ZU/IK+qpM2fOePRnfX291gfHttwj3+4cmOrqaq0PezyfvxMVHx0dVbFCW/SUa5XHw5novnbtWiFiXIs33nijkDGi1V1dXWVyuxyyMmnRas4n+TE8POw5pPLAAw949O7GjRulK3msnTK8YcMG2RNEpScmJiT3Vm4YOaLcLATxWXLlZncIIRQKlUHMgDPRhFCpFLdt2ybDgIYPUIK6mCBKA2jDhg1S4pywZDIpIeeGNTMzU5bcCfizedrNiWOlwNlTMRz72rVrJXysF9HS0qLmjqwdwtDf+vXrdXqIi3R+fl4L0p4IsInOwPJgdstD3scmNDIpfXR0VELJd5mfnxdsyZpFGzduVCIllejLL78MAPja176md+ZC7+jo0KZkkw2pHPygSqHA+fl58cxWqyX/uHlu2bJFp0D4fq+88oqq/dKgufLKKwE443cn9NbX10vuaTxZPvoRJrFjtIqdSoCyevr0aSUkf+pTnwLgGHJf+9rXADihSsAxDBjG4vwwyXl+fl5GEedweHhYPKOCt1Wi/RwfKZ/P692oKGtra7UpUDe0tbVJ3vjd6Oio3pM6hrxpbW3VJkrn7eGHH5YcU+ZjsZh4bY0wP8meluFY6+rqlLRKndHa2qrxMCRpHS2edOLcxGIxGYHf//73ATj8/dCHPlT2rImJCW2ofvHSzcdisSj5pI7fuXOnxk39cPDgQfzjP/4jgFI4q7q6WsYDk/a5Kfb39+uUkK03Rp4yHHTJJZd4HFy/iGONxWKehrrT09Nan1xHY2Nj0hXUvbfffrsMWCb1cjxnz56V08Lf9uzZo9A29+BKrZb8DM9Wqr4djUZljJBHfX190h3c5/bt2yeng2uLv1VXV0vHkq9tbW1abzZ0624HtRBeBqGugAIKKKCAAgrooqFlx0xszx5aY/QaNmzYoOPL9Izn5+fLmskBzjHZRx99FEAJLWBS14YNG3Q83EKARH9sryxaytbCXa51y3tls1m9Lz36pqYmWZf0uhoaGvRMJisfOXJEx72JUNmaR7Tcea+dO3fKS6CXksvlPEiPn83mSJxjel1jY2Oy2mmNh0KhslIEgONZ0pNkYjqvv/LKKzVnvH91dbXkhGONRqOSIb/DeaS5uTkhLrbGB70m6+WSZ6x0OzAwINSEY2QF3c7OTk8l4NbW1op9bIgWrIQHBpR7PERQu7u7hRbQi9ywYYM8RCIna9asEd/sMVLAOX7K0AnlY+vWrZ4wbjKZXJHEWDtPlA9b4ZzriLrDJuvbZsIMl5Bf9CwjkYjG8G//9m8AnDINfIZFtvysT1SJ4vG43pMylM1mJVvUkwDwjW98AwDw7W9/W+/HyvBEvIjGXnbZZUK4vvOd7wBw0CCbPgCUNwv1O8RFymaznmr7sVhMCcz87ejRo9Kl5Of09HRZrz2gtE7T6bSSYIkQTU5OKnRr++YRafKbj7ajANcT94+nn35aeo7vYtcsy0fE43ElcFMX8R4f/OAHpYMp79u3b1fCPvfFfD7v6ZHmB9lkdPLOIt6UJ6LmIyMj+s5GaRiSY40+m2LBBH7S7bffrt+JvE9OTi6pTlGA+AQUUEABBRRQQBcNLdmtth12Acfyo/VKL2PTpk1KXmLewNTUlJABFtzq6+uTlc+/pRX//PPPK7mWuUHxeNwTf47H4yvimdCzm5mZ8VR8LRQKsubpFY+Pj+ORRx4pG18ul/P0fSI6lclkZJ0zH+qGG24QokUaGBjweK9+dRImZbNZzSe9zaqqKqEB9I7Wr18vJIpVUw8ePCie8D0/8YlPAAA+85nPyKu21XV5P1tIzsaJ+Zsf/cj4mU6nPXMbCoUUkyYCkkql5FXQy06lUuKjRTABx+uy6BzgeCPuY911dXWSKZts6Kc3Fg6H5Q3yuZlMRu/3pS99SdcSaaVnvGvXLl3Hdcccn0QioXlknkR7e7vQMluZ113gbznJv5VyFOjl0Xucnp4WKkCUK5/PSya5Ptvb2yVbzH+xxeT4t1zDQ0NDyhchykLdZN/JL+LabmlpkY6g3unt7VUuJOczlUop34cJ2ddcc40QHqIBzJO47rrrJHccf11dnb4jymPR8pXKf4lEIh6dPTw8LJ5yn2hoaMCHP/xhAKUChlb38f2YAHz48GHpGaJ0q1atEiLI+1vEyXZ697PyfzKZlA5grmRfX5/kkQdBdu3aJR5QVwIlhIc6y/YjI7rDHKcjR45Ib/OZ5Kf9zg9+8h62dIDVe5Rdosu7d+/WWFjA+Nlnn1WldL73u971LgDOvsO+Y0QvL730UqFGHLOt5ryo91/0XwQUUEABBRRQQAH9lpJv3dljsZisWFrlkUhEVju9wu7ublnURIE+9rGPefo80XsbGBjQCSiiK3Nzc2XHgwHHa7F9w/wiWzzNXQiqsbFRXiCz0gcGBmSN2mPtzK+gBc556ezslCXMOQiFQhorLWfbn8gezV7OiQtbVh1wPCHGUMmHSy65RLwgQrNhwwZ5vUQHOjs79R09EY5ndnZWCAR5NDEx4fH27Kkyv3t18X72xBE/W1palLtDdCOVSolnpIGBAXncTz75JIDSPD3xxBPyJCmv/f39nmO469atE08Z53ef+lgqcT6z2azWB+9dV1cnNIOdxwuFgtYqy98nEgmhQPQ8WQRvx44dQmbZif748eM6QULZzufzK5KPZnlJeWK+Sl1dndYMUbnW1lbNNddpTU2NvEYiWpTrq6++WnNky+Vz/NRvtqedlVc/kALKU2Njo57H93zmmWf0XCI6+/btk+75wAc+AAD4gz/4A63ZJ554AoBT/A1wEB9bsgEoL87KfCLbvsa2SfCD7OlU6hvKy7PPPiudwj2jsbFR65LI1bPPPisd+tGPfhRAqSyB1aks5Dg5OSnkgOO24+FYK/URWwpRVhOJhN6Z4x4ZGZE8MsKxbds2oYyci+3btwuJtQgL4KAf1B/UN2zjAJSQoVwu52srJxLl1JZ5sSfoSJTNSCQihJG6dm5uTogQZcyW3+B6ps5Zt26ddAznoba2VjK0mIiPb8nN1dXVUiBUNlNTU0rU4mSEw2HVz+Di3bJlixQO78dk0GuuuUYCSsPj1KlTEiIKUENDgybNNiuz9W+WQvaoMO9vE4C5iLjJnzx5UkJHoW5padEGSLjT1pnghsnP06dPS5htjymSu7/NcsdmK5pSUBneiUajSkBj6KdYLEoRcQO0lYs5FwyDvf7662WwNeBsKFRO3IhsXxu/wnjuMEkmk9EzuOmvWrVKyoZHl2dnZ/Udw2BPPPGEEmI5Twwz1NXV6TsafidOnJChRNmxfHQb6ss18qi0JycndS9u4KtWrZJ88eh+OBxWOQKuyQceeEAGDxO4uWEcPXq0TC4AxziyvckAZ77cysgPo8BW/LW98QBn02MZCYYPuru7ZRhR1hKJhPQI5Y4GrpWD3/u93wPg6CbOJUNOPT090km24exyqoyTbFI/780QjU0T4FzbysDURel0WuFzbqbUr/fff7/GzUT1O+64Q/NEvWuTh/1OIbBhT+pS8iSXy2mv4Ma+fv16jZsJr0eOHNF+w+vIn66uLq1BGo9r167VfmOrjtuG2oA/B2KA0pzV1dXJ6aFOD4fDSnng+nzppZdkGNCBnJyclAyw5hKrrx88eFB7Hw2EVCrlOShTV1dXFpr1i2xYm2uR82/rMzFpeWpqSmuG6/PSSy/1yCd509DQIIOHenpsbExySr61tbVpT1kM34JQV0ABBRRQQAEFdNHQkhEfd6KUhbKtF0QvlJZ9e3t7WfVeAPjhD38oaJZWuYX06N2wgmo+ny9LWgMcC9Dd9Zq0FAuef2OP6BLJIbLR3d0ty5Njb2xsLCvaBDiwHb1iIgD0Mm+66SZdT3Ssr6/PU9DJVsL1u6AY4cPR0VFBj7S8BwYGBJPT21q9erUQHyIAtbW18haJajEcdO7cOU/Ptvr6evHLlimg9+auDL7cMfIzHo/LCyTk2traKnSKoYFisSikg55MZ2enQgEf+chHAJR67XR1dWlshKfPnTsnb4V8tKEWjs2NSi2W3AnUMzMznnEfOHBAMsRu8zZUy/V34sQJHUhgXzWuu1/+8pdl6Ah/I5ppE/25biohXUslInVzc3MaC5GNtWvXaqz8raurS4VDKadXXHGF7kMdwjXc1dUlpIrd3Hfv3q0EYa7dmZkZ6Th3gdPlIluU+/Hx8bLwLODoQoYkqUPT6bTWGwvEZbNZefk8mGBDRdQzlMOpqSkP0l6pfMZyyT03tggh0ZvJyUm9M0OWbW1tQuzIu2uuuUYyRdSAZOWDOjiXyyn5mes/FosJaXKvxaUSx2N1GuePIdOhoSHceOONAEqpAj/72c+EqN9www0AHNnm+qHeISL99NNP45ZbbgFQSqlYtWqVkDHq0WQyqTnzk6hrbPI018SePXv0PeW5qqpKuoY6JB6Pew7skEfT09PaMxjy/OUvf6mwOv+upaXF07Eh6NUVUEABBRRQQAEFZGjZOT42XksrkFb02NiYLF96j42NjfqdSZb3338/tm/fDqBkDdI6zGQyiusx96ChoUGeGS1i63m5S/gvhWhR8v6pVEpjpdV55swZfUfPftu2bcqhoIcYiUTkFdMT4+f8/LwQBdsOgN6BuwOvfbflemLuImzT09N6T75TXV2d8lj428zMjHhIpMD2VKNHSR7ddNNN4id5yDlyk7vYll95TBxjVVVVWcIv4HhK7iJ1zc3NKr5JJCeTyQiRvOeee8rG0dPTo3clr9avXy9PzfYFc/MtHA4va5zuZO10Oi3+0PNKJBLiNxG8wcFBeY2UqUwmI++bvHr88ccBOPF6IidMZMzlcpo7+x5EKWyxxqXKq7sVTW1treL6fE46nVbOCt/t8OHDZXLMe5AXzF3jXBWLReWnMVH20KFDQryYZHzu3DnJk82DWY6+sX36AEeurB4FnJwr5kdwrn/xi19IH1F33n333dIb/I1zcuzYsbJhqJNWAAAgAElEQVQWNbwXkQerE/wusGnXIIl6gehTW1ubkFYiP8ViUTLAY+39/f346U9/CqAkp5Tlqakp5bOxAGA0GhWCwOfb8h32MIUfOaGkyclJ6Q8iqalUSnqBn5s3b9Y78Prnn39eOpUIPPXN5OSk0BHm57W2tqqECscfj8fFZz8St90o5NjYmMbAXMj29nbtGURkbV7us88+q7+lLuJ6o5x2dnZqPdOGSKfTmhuu03A4vKS2MUs2fNzQdT6f16Llxjc+Pq5wAl9006ZNCvtQwG6++Wad32eohbDf4cOHNdn2tAaJymF6etr3CrgAyqqDcpGSwcPDw2V1UgBng2EYgGPZvHmzxkzYnAKdy+XKEsU4PoYNKjWW8zvUxc/6+noZa1xAV1xxBd773vcCKPEwGo0qhGB7sHGTo9BTRg4cOKCqqfy0zTp5D9v81i+qdDqMvGIi4ODgoDZGhgR27Ngh45NJh/l8XjLgPt116NAhGfc0gmtqasRHGiChUKisbpH9XCq5w7J1dXVaF9ysX3rpJY2XyuWFF16Q0cKTMZdffrl4wLAf5/Daa6+VwUeedXV1aUPhHNbV1em+thbMUjcU97pOJpNKfKQizOVySrLk9ddeey3++I//GEDJKDhx4oTqg3C+aNAXi0WNlX2sZmZmNB+VErX9qjDOd7anquhU8P3a29uVFEvdYo1mfrdt2za9KzdKboTJZFL6yRq7bl2wEj2e3M8ASjwgHxsaGrSPMKzT1dUl/jEZeGZmRnPPTfOOO+4AAPzgBz/Az372MwAlo3Hr1q0eJzKdTnuMAb/qMnEzHhsbk77huHt6emSskQf79u3T+9Mw6Orqks5l6NWG8Og8U2a6urr0LKtT/DqpZsdgm4TSuaBeicfjWp90ogYHB7UHcg/YvHmz6qHRkeG+093dXXbCEXAcVOodW9XcbYwthIJQV0ABBRRQQAEFdNGQb3V8CoWCPEpam/39/fI4iFwkk0n9zuOnzc3NStCixffggw8CcDxlJnsRPYrFYp7u7IVCwVfLllYkLduamhqhNPT6169fr/Hx2N6pU6dkjfKo9+7du5WgRU/A1nehp8wji4lEQl609Y78qm1DcndiX716tax3esXJZFK84Xhee+01JQPzb/fu3at3docment7dUSVfEsmk/JULATu7kDvlwfGuYtEIuIBodT+/n4lQdpj2oRhidIdPHjQU/WWfLfVirkOMpmMZIEITCQS8b0SrrvkQUtLi6cGS2dnpzx9epEbN26UF2y9KiZIErnj0eBkMqm/tSgYYXjbh82dGLscPrrrTYVCISEElJdMJqP6WVynl19+uY7k01N+9dVXJbPkDfk1MDCgcfFz3bp1ZboLWJk+cu41Mzs7W9YnEHBCH+7eap2dnQrnUBbPnDkjmaBO5Dwkk0kh1tRB6XTa0yNvJeTUXQm6qqpKfOFYa2trpVMfeughAMB9992Hu+66C0AJuRsYGFDIkqgB+X7u3DklQ/NeDGEDpfnMZrP6tx8VxgEv6pDP5yVffNbLL7+s8DHDX3v37hX6RTRoenpaupdI38GDB/XbCy+8AKBUKoaJ6UA54uPHGnSTRZcpM0TXnn/+ec0398qOjg7pIvLwsssu05qljiXf6uvrJeP8jMfjnpI1tuwJx7wQHgaIT0ABBRRQQAEFdNHQkl0XtxdmE9Bo7W3evFkWPa1eewTcVnr97ne/C6B0NJGWoO07Y6tR2m7XfA8/LVreixbl9PS0PD9aoG1tbbIymUtx7733llWVBBzPkugBj55yTB0dHbofLebZ2VmP52DH53cuE/MxUqlUWdwfcBKu+R1zq+xxXpvXxRgvvRn+3f79++Vdc25sJ+xKidt+5TGRbH4G55Zo4eDgoBAf2+vGXbLhmmuuEerozk/K5XLybijrQMmDt0cu3XLql9zaarFcg5UqAd9+++0AHBSAXj9z6qLRqMbNY/m2EjULqBEZjEajmgPbZ81PGXUjH0CJJ3x2c3OzJ5/l+eefV14B33d6erqsEjVQWrtPPfWU1iCRlUQiIYTofIirXzy01YTpGXOMc3NzSla2JRmIxHKMg4ODkk+OkbkWq1evFlpL/RsOh/Vc22PNb8SHZJOruS7Js+HhYf1uq4QT1eEYH3zwQa0z6hHeo6qqSjJL3VpTU/P/2fvu8DirK/13ZjQa9WZbspotF9mywY1iMDiG0KtpCSRAypYEsqQnT7bk2c3z+yPPs3n22WRLyJJsNiTedCAQSgKEYgzYgDG4N2wL27KKJatrpBlN+f3x7fvOnW/GoPLJTuL7/qM2+r5bzj33nPece27GHX2xWCytMr+XMJkkdyJ8SUmJ5oV7WjweF8vOm9jLy8uVL8icQq6/HTt2aL1RFnJzc9WPqWB5zOeaBw3IDLMdkUhEeb7c54BUCQxTT3If59pinuTy5cu1nrnHDA8PiznnXJr38Y0Hk76klDBPbVBRVFRUZJzSCYfDWrwU1IGBgYyr7c2qsaSYORCRSCTtojnA2wQud78AZ2Njhrp5ySTbwf5VVlZmhHz27duniaKQsKqzmcxnJhOa11IQU3EJq4mcnByFLdiW/Px80Y/82tfXl3b6CXA2TlKuVE5ctNkUjM/nyzgNNJX9My9GdBtXOTk5opxN45YbPw2+8vJy9Zsn8PiMoaEhGcmUyby8PPU726WrXikl93PM6wbMkIdZlRdwQpCs6cMTTrFYTLS6Wxa6u7vTLgDl890nIL2GO8k2EolknIIy62zxd2+99ZYodM7T5ZdfnlYdFkg5N3V1dWlyz8+4w1DmgYSpQkFBgdYHw5A+n0+bh3nVCA0jzuGbb74po4abDJ914MCBtJpghHvtTZXRY8Ln82leaICfOHFCIXDqyHvvvVdrkUaBWeWdThqN1rq6OvXfnGN3xfupnMNsxjHbWVtbK+Oboazi4mKF9qhjfD6fDpFwzjhOs2bNknHHdRcIBPRe6iCvHUg3zBsbuP6AlLyxz11dXWmnoQFHP3Ku6VDypFo8Htd88TMjIyNp1dvNr+OFDXVZWFhYWFhYnDHwLLnZ9BDMKrkmTQs4lhwtRHoyJl1Fb4w/+/1+WfK0YpPJpL736t6qk8E8as5+kfkIBALyntnPK6+8Ut6JeeSUYF/Y7s7OTvWFVn22e6qmkg0x6wK5awT5fD61j4ybee8K21pQUKD+0hNh0nZJSUlGQmi2uide3ZPzXjCpZ/YhFovJMzRDfWSwGAox55HzbiYyu/9myrXJ3E01W2C+w6SJOX+mN2jeNQY4TAfZBK4pyrt5hJj9yXZx5VQzk+b7zYt7zbIMgBMqMe/VA5xjzfQgGQbj3MXjcX3OLCPhTnw9FfMXj8f1HpO9Y9sZSmhpaVH7yQaQlQOQUQk9FotpzZoJ6GaI61TBDN+znWaNMLbv8OHDKlXA6vF+v1+hQMobx8FkIcgKmRexnop5zHYoJVslbB566erq0vF9rqmmpqaMS3Z5t144HFYkxNyj3H2aan1qwmSeKEecS5/PJ73CNRaLxTIuxWYExaxF5t7rgcmHJi3jY2FhYWFhYXHGwPtzmUhZmWZRQzMxkfFzWoWxWEyMEK1Bs2gYvWZ60mYOzKnwvgi3xxAIBNRuWuR+v18eJz2QcDickQxLL6C/vz/DezWLkpl3yEy19W7eLm3mVZhMG5B+XNlk2tx3INEDMCukmt6z+36cU+WdZLvLze3pDg4OZhSuM/+X3gf7nJOTk1EhdWhoKOMQwKlAtqq7pvxw/eXm5qrf9B59Pp++JzvJ/pv5Sab3eqrnD8i8K9CUJ/Ombx7dpmcJpPrlvk8ISI2DyXy6c0ImW2l7rHCvxUQikTHGQ0NDaWwj4DBe7hwv8zN8hpnQfCqZHnc7TASDQbFtlNMTJ05oTtmPuXPnaq7IEpj3p5EpMTGRCr9egGObjfHhgZD29nb1hyxsUVGR+sv/5ZgEg0HNramfvU7SHg/MNeEu7GvmdBLmXW3sH/NoTZ1MfWoWGJ1sPz0zfEwFaCYEu5OPfD5fRt0Rs5NuJWoKifmsU2nwEG5ll0wmM6pL+ny+tI2P/+dO/DST0NzPNcfodCOZTEpgzT5k29Ddm4abqgeyC+yp3DBNcLGZJfSzyZUp1+6/83/NU43uiytPJ8z3uw3sZDKZdpkif8f54EZizk+20PaphtnGbAcC2BcmrAPpl966DyQQiUQiY92ZyvZ0wQwTc07cJ5SA1PosLy/PCF2ZTtvpCGu9H9gW81JPM0xrOl1A+glUfo76dnR09I+qb9mu36EMsl95eXlK7DX1pjtU7j5VBUzdwZ7xwjzA4j7h/X7/817JyuY69Uqf/vFIh4WFhYWFhYXFFMM3HgvK5/N1Ajg8dc2ZMsxOJpMz3u9Df8L9A/78+zim/gG2j3/ksHL6f7B9/KOG7eP/4c+xf+MyfCwsLCwsLCws/pRhQ10WFhYWFhYWZwys4WNhYWFhYWFxxsAaPhYWFhYWFhZnDKzhY2FhYWFhYXHGwBo+FhYWFhYWFmcMrOFjYWFhYWFhccbAGj4WFhYWFhYWZwzGdWVFQUFBklcz/Cmht7cX4XD4fe9FKCwsTPJ2+D81tLS0dI2lGNWf+xwCZ0YfCwsL/2T7ODQ09L59LCgoSGa7b+mPHX19feOS0z/3PhYWFibLy8unukmeo6enZ0xyCvz5r8U/x/6Ny/ApKyvDPffc402rDGS754tfA4FA1vs53PfsvFchxu9///tjakdFRQW+9KUvjemzboy1EGS2+6vG8oz3u8/qK1/5ypgqa5aVleFTn/rUWD6a8W7zfqSx9Ne8dy1b+8dTPPO///u/x/zZsrIy/PVf//WYP2/i/drkviPK/fPJPj8W/PCHPxzzZ8vKyvCZz3xmzJ83cTouFSX+67/+a0yfKy0txV/8xV+M69nuNWXevTUWWTPvUjKfNZ67uh588MExf9aLPgLv3T53v72Y8/H0sby8HPfdd9+k30mY/cl2n6P7MxPVqffff/+Y2+TVvpjt8uST6ZlsFxGPF2PdF8vKynDvvfeO69nuO/2yyWi2uczWp4kWWX7ggQdO+rcpuZ3dRDahfK+LDnlJ2cDAAADnEk9eksmv5kV2p7vytNtQA1J9yDbpvLSNX2OxmC6s4y27wWAw7WJCPv90XebpvnQ0Nzc3Q5Cj0ahuveZlgRyH+vp6zJo1C0BqLLq7u9Xf09UvE2yX2S9+z/YFAgG1mRsqL03MtlGat2mfbjk122C2xX0pZyKR0IWI7BtlcWhoSJdj8v/y8vL0/em8GTobAoFA1v6Njo4CSK03XnJp3kzP9WmO1em+rBTIXCvmTfHsVywW0zy5L6HNz8/XTef86vP5dOmleYH06epvtj6+117Bv7EPoVBIbR8cHATgXOpqXooNZMr+6QDb6ff71S7uc8FgUGuQMsqvPT09+jzn1u/3q0+nu2/u+TJvk6c+icVi0hmUXSISiah//FtOTk7a5azAxPcOm+NjYWFhYWFhccZgShgfk4Kkhcavfr9fFh8t22QyKUv26NGjAIC9e/cCcCzimpoaAEBdXR0Ax8KlJ2ayBqfaQ0kkEhnvTCaT8kTYNr/fD8bymUNE67elpQU9PT16HgBMmzZNlj4Ri8VOCWtAS9202N0eUn5+vuaQbFVHRwfeeecdAMCJEycAAA0NDQAcSp9zTU80EolonPgs0+uZyr5me7abrcjJydEcmEwjmQD+jc8y/9/0NinX/N2pZkVMloeeE9sQj8ezsm5FRUVpv6PXPDAwoN8x5l9WVqa+mXM71cjGALgZVpOhYx/a29vR2toKwJFZIKWb6uvrMW/ePACOjPNvlFPij4H54byGQiG1n7Lm9/v1u2nTpgGAmKyhoSH1nwxtYWGh9BPZg1MFd7jK5/NJH7APRUVFahfX38DAAEZGRgCkGAHuD4WFhWhpadHnAGfOKB98/qlmYbOFqcy/sW/sR319vdq6e/duAMDBgwcBOPkrlEvKalFRkebRi1DRWOHeH5LJpL7nHBYWFkoG2e7R0VHt92QfqTuSyaTWLue+sLBQ4zGeEHY2WMbHwsLCwsLC4ozBlDI+ptdcUlICwGE8TAsOcOKVZHheeOEFAMC2bdsAONbs5ZdfDgBYs2YNAMfbbm9vB5Cy+GKx2JTnGri9+2QymRGjDIfD8qRoxS5YsAAXXHABAGD69OkAgNdeew0AsGHDBnme55xzDgBg+fLl8rrpqQ4ODup5bg/US3DuaKmbcVWezpg+fbrm89133wUAHDhwADt37gQAVFdXAwAuueQSAMCSJUvkebHfR48elWzQSykpKTktsel4PK730usqKSnJyN8ZHR2VF0JPhZ+vra3FWWedBQDyRNva2uR5Zss1yMZaeNknIN27IrPY29sLIMVIAikGp7y8XL/n/77++usAHG9z4cKFAIC7774bADBnzhw97/jx4wDS87emih1xe5k5OTkoLi5Oe2c8Hs/oazQa1ZwcPuycByAzWVtbq1w0rudgMCh9ZeYG8R1TuRYJU14ok9SdIyMjahd1YmdnJ+rr6wEAV155JYAUi/DUU0/hjTfeAJDKxVu8eLHmn+yB3+/PYK6nAm5mICcnR2uKfczJydH3bW1tAJyIANfgjBnOYVbKRG5urnRqV1cXAIcZo07lGMbj8Yz8qKmAe9+IRqPSB9TpoVBI+pX9KSsrw/79+wEAW7duBZBi2IeHh8WwUxdfcMEFqKqqApDSQdFodErXos/ny9BjgUBAa8aMcPD9ZByff/55fd/U1AQAmDt3rvpH9ofzNXPmTM0T95NskYmxwDPDx6Qo9fCcHAk2F1Fra2tGYmhjYyNWrFgBAJg9ezYAZ/ECDt23ZMkSPQ9wFjgnlos3HA5LmDgYJzsRNlHwWWxHIpFIO30GOBubWyn29fXh0KFDAFLCT4EvLS2VwmZIr76+HjNnzgSQEuB3331XISR3aMwrmMmdxOjoqPrIdtbV1UkoOU979uxBbW0tAOC2224DkBLmYDCo/m/evBmAs/lSOfP/ampqMijPaDTqOVXrNozj8bhkhkqnoqJCi3L79u0AHEXE9lF2aeSeOHECBw4cAJBagNOmTcuaNDrViMfjWgtmKJKbBpXG/Pnztelz3eXk5Ghe2A/KcW9vrzYlMxzBd3GzGRkZyUhC9BLBYFCbGMOQFRUV+r6vrw+AI5vsf2VlJQBg2bJluOOOOwCkG0OAM0c0HmjEBwIBGXvseyKR0Lr0GmYCLseQslZUVKQ1yN8dPHhQzseRI0cAOP3nHLLflL/+/n7J8KJFiwAAV199tXTPsWPHADgGw1SHZYPBoDZt87AHQ3Y0TEdGRtRm9nXfvn3SG3zG7373OwCOTqU8czx7e3slM3S0cnNz9VzKsFeGbLaQPWWmt7dXRhsN8xkzZqh9lMfW1lY8+uijACCD5lvf+hYAZ15//etfA0g5k6WlpTIczDXpPjzjhT41jYxsp+s47uY+3dzcDCBFaiSTSZEad911FwCHJAAco4j9ovFUWFioPnDf9/l8Wgum8fp+fbShLgsLCwsLC4szBp6GushA0Crr6emR5UkP0aQXaXknEglZ6PRo6G2Ul5fLW/nDH/4AANi0aZMYEdNKzuaheHlU2n0csry8PK1fBOliUv/hcFhWLj0qet0mPclnbN26FfPnzwcAeZuVlZXyDrIdS54MzDHi3NF6bm5uFvvCxLrVq1fLQ2Qbzj//fMyZMwdAaq7JgJhUOb3M5uZmhfbOO+88AE4SG9kseq+RSMRTxsf01skM+P1+hTgYEujt7RXTQ1Zn7ty58qTpedLbqKqq0vg89NBDAJwQwsqVKwGkPNrBwcGs9Wa8YII4TqOjo+ojqf62tjb9ffXq1QCAlStXam5IpVdVVUkeORaLFy8G4KxNeqq7du0C4LAqDFOT1SsvL1e4k/32ImnWTE6ljFGHhEIheYFMBN29e7c84LPPPhsAMGvWLP2dfSErUlhYKNaI67Orq0u6xkya5vdm3REv5pDPNdMEqONmzZqVwWqFQiElMPN3tbW1asszzzyT9vy8vDyxfBdffDEA4J577hHTRVbw+PHjaouZ5O+FPjUZeX5PpmXHjh3YsmULgFTo7qKLLtIcMPm8rq4OH/zgB9PazBDe0aNHpYuob9avXy99RIaoqKhIOtdMk/BC35jH1Dl+ZikIdyh6ZGRE+wZDsa+++qrWDcPo3B9LS0u1tqifcnNz9TvuPW1tbWkRCr7fjFZMBKbcc69gO6LRqNalmazMaAJ14uDgoOaCe9sjjzwCAHj55ZfVhw984AMAnCgJWSPKTWlpaUa40h15ygbL+FhYWFhYWFicMfCM8TGPy2Y7OmrGcslm0KPOzc2VB/niiy8CgBK3rrjiClnv9Cy3b9+O6667DkAqN2FgYCDj6DAwccYn2zFLd4Ep09qkpT19+nR52fR629ra5EHSiqXFHIlE1Ad63Q899JC8hM9+9rMAHC/afXwzEAhMygNzJ91FIhG1jxb49u3b9Tt6/mvWrBEzs2PHDgCOR8J5ffvttwGkV+n98pe/DAC48847ATjsEftNZmFoaEh9NBM6J5PL5C5MODIyIk/fTFBmjhnncceOHWJDbr75ZgDADTfcgA0bNgBIsRv0yFavXi3W6M033wTgMJ7sB73yeDwuOZ2qHAozV4vJ9DNmzBDrsWrVKgDOmKxbtw5Aik2dP3++csmYv0WGoLGxUbLP+T948KA8c37Nz8/PSD6eKKtl/o/JuLplt7+/X6zqnj17AKTyAICUF/3YY4+JUaA3unz5cgDOHC1dujRtjMLhsPrCeTPZK7PoqJcwj/OSFRgaGhJjzH43NTVJP5LBefXVV6VLmJjOPMnly5eLReY8d3d3S7eyKvOJEyeUQ8N1Om3aNM2/F/D5fBpTsjabNm3Cpk2bAKQSXS+77DKxXj//+c8BANdff72YYu4dZIMKCwvVZiZt+3w+6Squ8blz52ouvViLplyarBaTlsnoAKm9gTqzoaFB+oNMVjKZxHPPPQfAyXkBgO985zsAHOaHe6TJYFMOubeeOHFCY8B+s32T2TvMEhZc92YJAcoY56GoqEgySLl+8sknJZ9k+GknvPLKK1qLZIh27NghnUTZzM/PT2NJiffr26QNHyq2UCiUdoIEcBYKFS+VSzAYVNIajZeGhoa0JGX+LwAsXbpU/8uFeu6552qzZOKTqVjNxNiTXZfwfshWZ4HPIaXc09OjBUm6fP/+/aL5zPtNOFEUTJOO5xjx+fv375cwnX/++RoHJuJ5gWwVaaPRqBaRWbWYC7exsRGAI2BcWAz9zJkzR4JNOpLJzU1NTaJqN27cqGdQTqh0R0ZGMuqueGHYASnF1tPTI6OOm/f06dOV1EwDtbe3N40SB4CHH35YCYU0brjAV6xYof5Tro8cOSJjg/0BMo0xr6pym4Y5lSwVbH19vdYM+7h161YpnE9+8pNqO407t2L1+XxKlOS7Vq9eLQOSnysqKpLhNZmN5b0MJeoaKsJIJCLFTgOgoKBAY8zPNTY24qqrrgKQ2ojYz3A4rOdyXqPRqPrHUElBQUHaydX3a+tEMDo6qrGmI7VlyxYlkC9btgyAE5qkrmQ7CwsLpY+ogzgmixcvVkj2pZdeAuDICNclE0qBdN0KeGfcccxyc3M1bnT0AoGA2vrVr34VgJMOQPnk4Yi6ujrNG3Up1+uFF14oeePYVVVVSQa4x0QikYyQ02TTCNxykZ+fL2ORv2tra9P88HfNzc2abxoQVVVVmm/2jae8qqurdWqWe/BFF12U4dQdP35cxof75Op4YY4J99j29nbJE782NDQoXE5jrq+vT3qHY9TS0qJ9//Of/zyA1DzU1NTgpptuApA6CPT222+rD5TN0tJSvZfPzc/Pt8nNFhYWFhYWFhbEhBkft4fj8/mUeEVPPjc3N6PS4okTJ2TV0QO95ppr5E2ZrA7g1KGghc6Qg+mZ7du3T7+jZc13kXocr/Vu/o9JqdOjpZcci8XE7rCN0WhU1jAt60gkknFknR7xG2+8oc/xKN8tt9wiFsS8u8z0lNimicKsdE1PrqSkJIOtamxsFDNC5mf//v3ynviM4eFheYtkVDhfixYtkkf52GOPAXAYMjeVX1lZKe81Gz07kT66x8i8x4fvmjNnjrx/ym5nZ6e8CnqWvb298rI+97nPAYDCJq+99lpaQiz7wO/JgvX29qrf9OImW7so21qkjLAPnZ2dOqLNkFBdXZ1COqwzVVJSovkgg3XhhRcCcOpoMFzAft1yyy1iM7mGw+Fw1orW44WZIGr+HIlENIZsRzKZlHfJZMjOzk6FCCi7N954o55jrmM+i2NEpq6pqUmyYdZcMe9TYhu9KC9hsq9kCdnHlpYWvZfjunv3bjHQ1C1LlixRf8lMUh76+/vlGZMVaG5u1hxSHvLy8vQ86oTJsFpm8rdZe4mMIBmC5cuXax4Zft68ebOYD4a3jh8/npGszItCBwYGFBIj63z22WdnsNmFhYVqk8nIsr3jhcncmswP9TaTfyORiL7n+9966y2x6GT5b7nlFoXCuH+Qdb/88ssVOeE85ubmKi2BTEooFMqoQD8Zdtl93D8YDGo8OYerV6/WAQqG6h599FExeCbjygMuXEeU182bN4v5Y+rEG2+8geuvvx5AKvze0tKStgbHCsv4WFhYWFhYWJwxmBDjk0wmM7wx894fWpZmkS8mMW3evDkjt6Orq0tHEcmW8BkdHR1igWjtzp8/X3kITGwrLCxUvon7frCJ9I8eq3lUjkwGv4ZCIXknZHCOHTsm5oae2ubNm+WV3HLLLQBSFnxfX588NrJcn/rUp2T5Mu47MDCQcT/JZPNC3LfllpWVqT9mIUkeiWV/Zs6cKW+LbU8kEhoD9s2cDzJznMsFCxbIe2DcOj8/X56nV0mUbi/A7/dn3Jc2f/58ySplctGiRRnVXM877zxcdtllAFKM1O9//3sADvPjvjOpqqpK42PeiO6BlKwAACAASURBVO3OexnL8cv3gptVMZMsmSu2a9curUHOy/Lly8Xc8VBBNBoVE8I54Lru6+vLKJaXl5enPpIZGRkZmZLEbbPyLfUE5SkUCqlfnMsXX3xROSFMkPz9738vlo65AVyvCxcu1GEM5lmUlJToXfQyzb5NVaXxQCAgeSLrWVlZqWPdfO/TTz+tcScbedZZZ2l9su30mhcvXiw2iwxlaWmpcpo4TocPH5aeYzvMUiQTgTvx1zx+zXbG43F9//LLL6vtH/rQhwA4h10AJz+P+XZkDTgvGzZsUIL0DTfcAMBhUdw5UyMjI1M2fybjyXE078jj2mJ+59y5c6VvKI9z5swR207Gi7r10Ucf1ThStx48eFDsHL8WFBSI/TMjIROBz+fLumdQZ1M216xZI5n50Y9+pHeTwSPbtX//fsndq6++CgD45je/CcBhrJjXRdugtrZWbC4T2Q8fPpyRJzYW3TMhjWsqVpN+dm8UQ0NDot4ozDk5OVJW3AyeeeYZnVZg+ItZ/o8//rhCEhykrq4u/T3b5ZDuUNd44ff79VyTuuQAc9ObPn26lC0Fs6ysTMLKkz/Nzc1K7jVrrQDOxsQQEUMKCxYsUF94OuPw4cPaMDnBE03cdvfHNBTd9WxGR0elRNnXxsZGLTYzhMN5Yvv4twMHDqj/DKmsXLlSwk7FkJOTk2EMeFXDh33Ny8uTEcq+dnd3K5zFTaSsrEwGDCnoRCKhfjz55JMAUnK6aNEiLWxS0G1tbUqMZr/8fn8G5T/Z5GZ3WMkMdZmySPr74x//OABnvtevXw8gVZfo1ltv1RwxJGYaGWZYEnBodvaXG4uZ1D9ZmCEkM/xM3WGecKSRx2TXjo4OzQnn9dlnn1V/uMlfc801ABwjh8+jPtq7d68UunmFibtNXvaXX7lhUV7POuss6QAao2YSPuXplVdekT7iGmS/qqqq0gw9wBkbngwz9ZOXpw9NGTev+TGrggOObmfohsbaBRdcoNAJwynr16/POM3DZzz33HMKp3C8mpubMzZ+04H34iSw+b/ZDCrKXSwWk1xyrbW3tyssSwfy2Wef1fPYN+qTjo4OEQFcp/X19UoI5ufa2tombfCYcFegLy4u1gEKnsKrrKwUIUGj6JprrpGR94Mf/ACAc9L0ox/9KICU8UaZv++++6SfKcs33nijwl/UyS0tLZo76qSxwIa6LCwsLCwsLM4YTPo4u3nsmZa3eaydnhZDBCdOnFCdDdJxM2bMEIXFY8X0UNatWyePhtRsNBoVXcb35+XlZVi2iUTCsyQ1v98v74GW66JFi2T5ku7PycmRBUzKPRKJyDqnNU+L2ExiJD37zjvvyHrl+MViMY2rF2GgbEnfwWAwI9nvtddek+dHr3Dp0qWy0OndL1++XP/LMCSfsXLlSrFBTNY755xzxBBQHszj+l4zPWZCI8ePNHt/fz/eeustACkPbP78+WJDWOOmo6NDsshQCJMt16xZozAJPdbi4mLJOMeiu7tb7/fqCHS2hEqOH9m8WbNmyVti8uRvf/tbraO1a9cCcLwqHnOmjLIP9957r9Ygw0QbN26UR8b1X1BQIHbEHRL3AsFgUGNIz7aoqEjjTpbrwgsv1HwyuX7OnDliPKiT2Nauri6NF1npqqqqjDv6BgcH39OznwzM6tTUFdQBkUhE76WePP/88xV2fOWVVwA4Sc7uqtuct+HhYbHwZKQbGhrSwvd8P/UddZtXVfCp2+PxuNrFd3R1dSmcQ3134MAByRE9/XfeeUc1wXi0n3rnwx/+sNgHskZbt26VLHDsEolEWq0nYHJymk1n+Xw+9YNMV0VFhfYQ7hW1tbXSQfza3t6u9AfqGerMVatWSS+TnZw3b572GfOibP4P++aFbjWjDmatJMBhmdi2iy66CIAz5jzYQjm94oortC9wjK699loAwBe/+MWMy3RXr16ttpPVPXHiRIauMdtyMljGx8LCwsLCwuKMwYQZH7eXmUwmZdHSYgdSx2l5TNJMKDOPSTPhjklLfMbIyIg8aeaYHDt2TN46PYZsCaJexGrN3BB6g4xDVldXy2tiUuzChQvlbTC+yTYCKcuWVSkLCwuV6/Lwww8DcI5gMv+AMI9he9E/M75NDywajcq6NnNDyHKQKRgeHpanzT4uXbpUzAj78+lPfxqAk/TGxFrGo4eGhsQkMJbb2tqaNQ4/Gbj/Pzc3V3kC9KTb2trEFpgVR+mNURb9fr+YDnrG7H84HJYXQplZsGCB5JR5UrFYLCM5fbKetLtoWigU0ns5d9XV1fKuKLP79u3TcV/Old/vV84ZPa67775bY8Pf8Z3mre/0/KZNm5b1DruJIluCOuWP3ns8Hk9LSAYcJoPvJ/s6c+ZMjf93v/td9QFw2D4+l3c85efn6x30Yv1+f8b9R14cZTefEwgE1A8yLy0tLRpj5gNWV1fr6DaZnw996EPqN9vM/JFoNKr+kmXZt2+f1iJlJCcnR+uDjMFkYJbPIEZGRuSts521tbVihcm6tbW14amnngKQSky+7777NEfULcyh+eQnP6n//fa3vw3AOf5OxodrNxKJSB97kQdjls8wCyO6q1MXFhZqPsjulJWVac0yif6aa65RLhD3F87ZsmXL9FzuR7FYTLJCxq+7u9vTW9n5DI5bMBhUX3lIpbW1VXqUyeibN29WDh4LvJ5zzjn4xS9+ASB1pxxzufbs2YMf//jHAFI61u/3a7zI4HZ1dWm/Hc9hkUmHuigowWBQQsyJCIVCovhJpQYCAS2kp59+GoCzCdKouPrqqwGkBuD48eMyHLhw6urq9AzSfEBmQuxkEn+zbZhcMFSEfX19UjZMIpw1a5YEktTrww8/LIXqpgCXL18uYaZRsH//ftHxpLvNS+XcSdyT7SO/joyMqI4JjaFYLKaFyFDcgQMHtJhY6+W1114ThUmDgUIfCoXwz//8zwBSC3hwcFCLmgKbm5ur/pqnBScDtwzk5ORIudOQHh4ezgix7t+/X4nMX/rSlwA4xhA3DSb0mtc78CQelU9FRYVkkhuvafh4dTrPDXPTotwVFxdrHVFpdHR0YM2aNQBSRuAf/vAHtZV1UShnX/va17TxULHm5+dn1EAJBALSBebJzokg21UXubm5Mgo4vqOjo9q82c/169enXZwIOKErtpenhvi3NWvWKJzLtV5cXCwlz43V/N7rqyqIUCikPlI/HDt2TJsHk0IrKirUR7OOGb/nVxpMxcXFCrPQ2O/s7NRY0BCeP3++5tCdwjARmOkDZjI+9TjnbsGCBWkJvwDwxBNPqM233347AMcIp8FHA5Z1h2677TbNKdeieYmyeTGp12vQ3cdYLKY+mtWkuQbZx8bGRulDOmbJZFL7y7PPPgsgtR8EAgGRCXxnf3+/ZCFb/TMzLWWyoCzEYjGtcdMBohyZ1ajZL85va2urwuoMYdIoeuWVV6RrzJo9v/vd7wCk0iOKioq0BsezH9pQl4WFhYWFhcUZA88uKU0kEhleWCKRUM0MJkpWVVXpcwz3bN68WVYbvTEmz+7fv18sAb2CVatWKRGW3uBkPcuTwaw9wZAHPcq2tjZZtGRozj777Aza+LLLLlO4jowKre/Vq1enVbAGHCuZFju9vWw1NLy648kMB9DD4Dzk5+crFMUqnFu3bpX1zrpEo6OjOvZLdo/t3bdvXxpDADgyQpaM41pUVKTQqOldewm/3y92h4xPIpFQaNG83JFtpid55MgRsV4MB911110AnKOUZIPIgpn3LTEMk0wm0y7uZJu87iPXID3fI0eOaM2wTbFYTCwVPzc6Oop7770XQGp8mJS4bt060cqsq9LS0iLPjEzvtGnTMo4aJxIJz8JBQIppIaMViUQ0r+wL2TgAuPTSSwE4a4zzxLAuafnVq1dL1zAB2DxyzTUxMjKSkTzuFczkZjIubGdLS4sYboZ+Dh8+LK+ZicxPPfWU2kxmgWxCaWmp5I+s+rZt28TWEpT5qYCZZMt2UgfMnj077Ug/4DAI1BvUrdu3b1fYlawW6/k8/vjjCo9QTufOnZtxnL65uVnfcx690qnsVzQa1fpgH6urq9PujgOAv/qrv9L6JPt28OBB6SDqVu5zmzZtkq6kzG7ZskV7Ew/H9Pb2Sn7MWxS80jnBYDAjXDg6Oqr+Ue+VlZUpNMkxTyQSig5873vfS3vu66+/rjs6KdcHDhxQOgGfX1VVlcH0jGUOLeNjYWFhYWFhccZg0snNRCKRkOVHT2V0dFSxO/7uuuuuwyc+8QkAqfjr+vXrFR+kpU4cPHhQ3j+fNW/evIyj5V1dXRnFvSZawDAbcnJy9Fx6g/39/fKKzdwUemVkgS655BJZ/UwApoc1ODio+DurJRcUFIjxYWG5vr4+eQxe9cntAR0/flyJr/QIrr/++oyj+Pn5+aqIymPQW7Zs0fgzT+b+++9Xfz784Q8DSLF877zzjo6aEjNnztQzGKueTF4BkJlHE41G09gNwGHpmOtCPPPMM2Ju6FmFQiExcJQ7JnxXVFTIU6N3Njg4qGQ8yjdZCWDyFZvdMAtS0nsk67FlyxblLF155ZUAnBwsxszJDCxYsEB9IzvJPIQ5c+bgjjvuAJBKIDbvqyP7EgwG5Xly/ibjYbqLBZpFIMnCjI6OSo6ZE9DV1aXPMZ/l+eef1/rl5y6//HIAjjfNxHwytIsWLVIf6G3H43H12escEbbXTJSl7hgaGhKLzD7k5ubiYx/7GADIQy4sLNTcMQma3va6devE5rAybiQSwQsvvKDvAWdczTwOL+DWW9FoVGuA8rJv3z7ls1B2zfytn/70pwCcvDwyVl/72tcApNbY//zP/6iPzM8z2XnqZ5MZJSY7j+48TLPoJ5mJCy+8ULLH4+rBYFC6l88oLS0VU8dyL7/85S8BODJI2edzW1papG/IcI6MjEjfeZXAbaKgoEDsv1lpnKw/2zh79mzpdO5pw8PD6hdzXn/4wx/qGSw3wbzYd999V3YEdWx9fb30znj6ZRkfCwsLCwsLizMGE3Y53da7WRiLccmSkhKxBYzRhkIheU5kP1566aWMO0DooaxZs0YWJfMr9u3bp9/Rg45EImnXAmRr40RgFkOkFcscgZkzZ4qtoTfx8ssvK3eFVvdll10mq5WeADPbe3t75YHQg5k9e7Zybcx7ZciG0IPwijHguPX19akftKLNgoy01CsqKnQCjV5ZV1eXmAGOCfO0EomEmCHGa3nLN5BiT8rLyzOKxUWj0UnNo/s6h9zcXMWdyd7U1tZKnlhWoaCgQLLF/p999tnynnjFBU+K+Hw+xdXZn2g0KqaBDIxZONI8EuqFrJrFGk2mB3Di4/SSyGT19/erzSxfUFRUhIceeghAigW68cYbAThHiCkDjLUfP35cjBifFYvFMm6C9iJni8+KxWJpxUyBdMaX/ayoqNDVImRA/H6/ZJAyQRZl48aN0mHmsW7znjUgPa/BPCHkZW5IPB6X7PC5c+fOFSPO06979+4Vu8GvGzdu1P9++ctfBpAa/z179kiP8XfRaFRzSD3d19eXsXYmW6zRLeORSETrnGuxo6ND7SPLU1lZqbbyNGV5eblOAPH4O48/19TUiIklc/fqq69mnDRMJBJZT416UZSSbHI4HJZcmtfXcH3yOPfMmTOlU7m2GhsbxQxRt1KnXnzxxcpp4u96enqkA7guzKKw5r44UVnlHHIsg8Gg1gp16ODgoHJwzLI07DPzKBsaGqQnfvaznwFI7QsLFixQ7hLnsLy8XLqIMmLmTJqRpvfTp5M2fMzwD+lvDvDZZ58t+pGK58iRI1i3bh2AVFXNzs5OLWgqalJk1113nZImaVA0NzdrMzIr8rrv7/EimdKs00GjwLxzhZs8B/2FF15QO5k0uXXrVilUboo8ivjGG2/IKCKOHz8uY4jj4PP50o6rTgVKS0u12fNdu3fv1tFBLsijR4/quCINs+7ubilj0us/+clPADh95Fxzw3ruuef0Li6cadOmSci5AUzWIDANV8BROjSgGTptaGiQoqRyisVikl0qn1AoJEXNvzHxNycnR1QvFXZbW5tClualhNxczIRKL0C5iEQiWgvcUMxQE+nwnTt3qi4R119TU5MMH7aTd3vl5eXhwQcfBJCinxcvXpwRgu3t7U0LN3uN/Px8rXEaYoODg6oBRnkaGRnJCEWff/75Upq8wJQJ3qOjowoH8lmxWExjxD5XVlZqM/OqFpMbnZ2dGWtg8eLFWjNM7N25c6dCCDR8zPuLqIuoQynfANISRd0Xog4PD09ZdWoz8Zeyw3U1PDyscDjDQE1NTUrm5tzNmzdPjvN//ud/Akitu7Vr10pXM/F7/fr10sc00AOBQEYo1ivjjsZVb2+vxpR7RUdHh2q28dDP7bffLmefczQ4OKjLg6kXqUeOHTsmUoGVq8PhsPpDR8b8H3dtuonALe/BYFBri+0OhULaF2gMlZWVSfczvFVRUSEH8oknnkj7fF1dncoVUEbuvfdeOW2sGbR7927pGn4123cy2FCXhYWFhYWFxRmDSTM+ZoFCWnQ8PldVVSUakpZdX1+fPCfTumN4jEX/SN8tWbJEljo9uaNHj4qiNJMs3YXUvIB59JgWLcNQiURC1i495gsuuECJWqTc/X6/xosJzDw+vWvXLnkgZJISiYQsZiIvL09ekdd3PNGzr6iokEfJuTx06JDmi2Nx7bXXyiMmNTlr1iwlo3HO6T339PRo/pkA3NvbKyaF85pIJPQuevRe9ZGMXCwWE4VK5qOzs1NtoWe8c+dOeWOkbXt6etJCPECKBTBDvQxxBgIBMQOkebMVFvOiurH5nHA4LHnj2gmHw5IvVo3t7u6WjLIw3MjIiObW7cl973vfw+OPPw4gVUBv6dKlmluOK5Dy0rw87k359/l8aTfb86sZngWcdcLkUIa3Vq1ahV//+tcAUpQ7mYWBgQGtY8pNd3e3ZIcsc35+vrxo9s+rBGDOUXd3t57JNVleXi5Z5BwCyKjwXFlZqfaTaeWaXLJkiZgFym5fX5/YEjLSJSUlaotXDLq7yrVZaZhy2NraqvexD7t27ZKHT/0ZjUY1Bpwf6p8ZM2aIISG7W1JSovnjeA4ODmaUXfAKZjjbrdNGR0czqsfffffdaj9Ddo8//rhYaa5FhiRjsZiSwBnyWrJkifYms2giZdWLkKXJnAOO3qNO41o4ePCgmDkyrlVVVWn95zPcBX3J9lVWVupzlI3GxkY9jyHPsrIyvYufHwuDbhkfCwsLCwsLizMGniU3m4wL704ZHh5WDJ4W66xZsxTjY2Joa2urmAPG02lRzpgxQ543PWqfz5dx6/bw8LD+x6ucCb4LSFnmQMor2r9/vzwlelSXXnqpYu60vo8ePaqYK/vMYoD79u1Te2k5Dw4OykonG5Kfn5/1HisvjiaauSksVkjPsre3V5/jke/LLrtMc0IcP35cyXnMmSA7UlpamnF0vr6+Xl4P81BMVsKrYnfuuHYoFJLHx691dXViRsj8AMgomlZVVaX/4dFhlix49dVX044dA46Hwrg+n2X20WyjFzJLhiCRSEhWzMJ1TMqnFzl9+nQl1NOT3Llzp+aIrN8DDzwAAHjkkUfkkTHJMJlMKlmcMhMMBiXLbMdkWErzmD7gyBA9dHqDQ0ND8vzJFr/++uuaL87h66+/rnvTyO6YeV1MIiVjUFVVpf81r1FxH/UOBAKeMXeAM65uBruyslJ9JCuXTCb1PXM9mpublYtFBpP5ILfffrs8Y5bUGB4eTrujDkjPF/GKzXLDZENYGNPv90uP8GhzZWWl5Ij608wzpO6lztiyZYt0L+V/2bJlmm/m58VisYy16FUBQz7DPNrNdbJkyRIx/lwn8+bNU7/JZsyePRsXX3wxgFTODtfwiy++qH2G/QoEAlqzHNecnByNi5dFGs08V37PdXXs2DG1l3v2vHnz0q7t4e8uueQSAClGnOv5xIkTuOqqqwCkDkvFYjHl5fFdPT09ej916FjW4qT5PSr0GTNmqLNMzG1ra1OHqKiWLFkiepMGUl5engwjLmwK+JYtW2QM8aRCTU2NOstNc2RkJE3xTxZmPQ3A2TC5iVGZbt26VQYbhXr27NlKsuLv+vv79TyOBwXCDC1Q6bS0tEhhcTyynRrxuuZEIpHIuORu4cKFGn++7/jx41qAXKydnZ1KuKQCZpLzOeecI8qZYzgyMqJFyj4ODw97XrGZfWS/SkpKlMhMmVy1apWMOm5yt956qzZB1iAqKipSxWbzIkzASWqnYuH/FRUVSQGxX+Y9VpTX0dFRT08EhcNhLXxS3nPnzs2obLx7924Zp1S2/f39MmBoBDNR+tprr1VSPtfrG2+8ISOYGyrl2Cu417MZIuE81NfXa80wvNPc3KzwG7/W1tZqI+KpIIblnn/+ea1PGra1tbWaG+o3jg+QeWpwsuAGn5eXl1Fxt7u7W99zfc6dO1fGN/XN7t275Ti5652Fw2GFm9mPefPmKSzNOTRPdRF+v98T3cq1kJOTIx3AOaiqqtKGzhDq6Ogobr75ZgAp3bJhwwbpTY4TD2EMDg5qTHjgorS0NC0Rnu1wh0wnC3dF79LSUq1B6oL+/n4lolNX/L//9/+0b9IhvOSSS/Q8yh7nMZlMylnhZ44dO6Y5NdMTKDPuuywn0z/O4dDQkGSGfZkxY4Z0HA27oaEh7d/m/ZN0Unj4icbRqlWrZAxzvT722GN6BvfTkpISvYtfx7IWbajLwsLCwsLC4ozBpCs307MwKWFa0SMjI7ICzfAQvWY+4/rrr5fnRuqLVmRLS4toS3ov1dXV8jzoHUQiEU9DXG6Y9/OQWkwmk/JY2M+Ojg55JfQaTRaDnyOamppk4bPPfr9fY8M+A5mW7GQpSzPJEHC8BFL89MASiYTGmMl027dv13yRmaurqxPlzPCJefSQYSAydKFQSHJCDywWi2XcIOzVnJrVmplMzpo9ZqVhhoE2btyoo8D0oqZNmyaGi2yW6UXRKyML6PP5NH/mMVd337yu+huPx8XSkI0pKytLq6/FfjPBm+uzsbFRTIh53w/gMD8ME5ApyhaqzcvL86RKrLtfZgVaygw9W5/PJ9lh8m5dXZ3aTg+8q6tL4Q+yj9RHmzdvVhI0x2rGjBliZ83kUHdY3Ss2hPJUXl4uD5b9Lisr0/fUu2+99ZaYViZ+1tTUiGVgqJxlQtra2sR+mUf3OU8c12ypA5PtH2XCTLbl/LFq8dKlS5WsS70ZDAb1brJ5PT09SnhmGI99bmpqUp00rr+WlhYxQmT1RkZGMhJ9JyuvnD+zdg9lieOZk5Oj9Ubd+8orr6gfZLdqa2t1nJ1rlqzmVVddlXFPpXmIxjx27o5eTEanutMjzDpXfM/BgwcVEr/pppsAOPrFLKPB/2VJApa44edXrVoldodhrQMHDqj/ZMwmyrRaxsfCwsLCwsLijMGkGR+zaiKPC5L5qaio0L1AtGw3bNigI+u0iq+44godAaZlT+swFovJumPiUygUyrAyo9Gop7c/u2P34XBYngKt3ZkzZ8prYnsjkYg8X1r6AwMDit+y3cyNys/PVx/Mqq30HPg703L3Cu7ifgMDA2Kd2Ae/368YOpm3UCik5DwmRZ44cUJ941iQIers7JRXwjnMz8/PqLQdj8enjLVjv3p7e8VmkdEwEypZrXjnzp3yOJlr0N7erjaT6aKX2dfXJzaLv+vs7JSHYh4D9VJOsyEvL0/95Zw9+uijYkLMW5opo8znycvL0zwy/k4v27xhnXNWUFAgBpTrwiz06AXjw3dS18RiMTEfnI8DBw5ovugdNzU1iT3g5zo7O8UysH9c10uXLpU8kw0yq8Ca8potP84LmIX02AbCPHJNZvbNN9+ULiG71dDQIF1MtpKfLywsFNNJeQgEAmJ1KcPRaHTKkpopJ6askYU6cuSI5o/rNBQKiSmnbhkdHcWdd94JIP2IO+DoYDKSfG5bW5v+bsqwV1Wp3eDzysrKxO5wv8vLy5OsUlc0NDQoUsA2PfbYY6poTBaI97Jt375dLB7HcGRkRCyh+34783eTAdczZbGgoEDfm3lN5r2TgMMCsXwE94LGxkZ9z/2f0YKCgoKMuzFLSkpkW3Asg8Gg3j8e9sezS0qBdNoZcAwfGgYcgHA4rI6Q8jTpZAo4F3FRUZEWAgfCvDDU3DSnAqZiY5uoELq6uqR02M+RkREpDyYR9vT0KJTiTso0M/HN2g/uOjZTuVlm25TNhDzzQjgAOO+885R4RjrymWeeUbI6+8NNZ9GiRXqGWWslW7K21yEu89nsK+l8JtmZJ624eNeuXauwKz+3d+9ebSAcJyZ519XV6RnmonRXhjVld6qQm5srBcHk64GBAbWd7ZszZ47mg2u3paVF4SyGEjhe9fX1mkezwne2+lJTYcCaoRf3RbPhcFhzwXbv2LEjQz+UlZVJKdNgYziovLxcOsk8NMEQple1pcYK9tE84MC5oLGWl5enkPr1118PwOkHN34aCmbohUmxpjPA+ec4TbVxDjhrge3i5t3c3Kx300BbuHBhhjG0ePFiyTb7ykMYQ0NDMhqznSrkGjfDo17BLffm883wEGWVunL69Okae4bb33zzTTkkHAuzZo1ZSwdw9BTn1LzeaCrWolkfzU2CzJw5U99zT9i1a5cMNR4uqays1Mk8yiSNxGAwKN1EBzUej2fUrOJ6HS9sqMvCwsLCwsLijMGkj7ObNLDbW3j33XfTQgGAk0BIb4UW+9GjRzOOeWe7kJDWnXm5HL0hr5IL3TBZCfaVoZ/BwcG0yr1AOvVmJivzd7RizeRsM0GS7zQr0vLrVNx7xPcRbjYimUxmHHEvLy/XnJi1W5gYSoaEVHplZWXGPWNmWMusDDtVoa5sCZqUydHRUf2efWxsbJSHRqakt7c3Qwb4f3l5eWISOMfmPLovtZwKUH5MeeO4kwECUuPd39+veTQvhWV4jp4Wmb6Kigr9zUyQZp/MPKqsFAAAIABJREFU9T9Vsgqk31vHdtfU1GTcGdbX1ye2hpR6bm6uWFquWf7fwMCAfkfPGsisYzOV4UqTYXaHK5LJZEa4u6KiQnNh6lAyCuw3MTo6Kp1sHpc3K9RPNUyGwB1qysvLUxvYvkOHDqWlHLAfLMFA1tndVyCVUmDqFjO1YCrlFEjXrWxff39/Rl2e8vJytcuMAJBZpTwyPHv06NGMOx6Hh4ezzuNU9tHv96ddQA44rCrXJROTt27dqjZxHLZv356RHkDWPDc3V583GUr3PYfAxNhly/hYWFhYWFhYnDHw9IIS982t0Wg0rVAf4FiDzPdhvkAsFlNyHRkceqhmUq/7K4AMZmQq4fbe2T4gxXIkk8kMq7uwsDDDQyWi0WhaRVr3u9zvmUr4fL6sbJW7aFVra6vmgPPW0NAg74QWuultue9pMT2SUzF3hMnCZIu/E+3t7eobvw4NDWXIG+csFApl3N9k3v58Kvtowjx+6q5Cbsb/OZ/l5eVqMxk78zOUc3ONE6eCLXCDa62goED9YtuqqqrkUZqF5dzzRJilIyjrpq6ZSrYuG9wyNjIyonYxLykej6uNLNAXjUalb905EMFgUJ83Zdnro+tjgalvsuVscG6Hh4czbk/v6uoSM8KvlM14PJ5RKR7I7NOp0KlmG8yEfLaFOS25ubkZScL19fX6HeWYydrRaDTj6LoZCTlVfUsmkxnjaibGcz6XLVumfjHS09vbK1bPPHwAOKw5Zd1klNz5hBONhHhq+HAizMRDt8I3KXeiu7s7g9alcWQKcbaw06ncULLVXeHEmu3g9zTizM3W3Refz5d2cuu93nUq4L7U09wwTcPHnTQ4ffp0LeJs85XthMjpMgbc7zVPdNAw6+npyRj73NzcDOOXP4dCoYx+nw5D4GQw+2Iqx2w1hcwkTPNvJqbqxM9kkC1ZnmEg03hzz0+2/mWryHyq5zPb+9xz4/P5ZORkS77mpkHDIps+OZ1ySv1h6ko3kslk2nUEgDMv3DT5N/Naofc6JHGq9Y67NlkgENA+mO3UFefKTBzmnkonbCrTAiYKhon51QTD5UD6SemT6ZGTXSDrNtonChvqsrCwsLCwsDhj4BuP5eTz+ToBHJ665kwZZieTyRnv96E/4f4Bf/59HFP/ANvHP3JYOf0/2D7+UcP28f/w59i/cRk+FhYWFhYWFhZ/yrChLgsLCwsLC4szBtbwsbCwsLCwsDhjYA0fCwsLCwsLizMG1vCxsLCwsLCwOGNgDR8LCwsLCwuLMwbW8LGwsLCwsLA4Y2ANHwsLCwsLC4szBtbwsbCwsLCwsDhjMK67ugoKCpK8++ZPCf39/QiHw+976VVhYWGyrKzsVDTJc7S2tnaNpQpnQUHBn2Qfe3t7xzSHgDOPvCj1Twnd3d0YGhoacx/Ly8unukmeo6enZ0x9tHP4x4uxziEAFBUVJXmh6p8STpw4gcHBQatv8Oe5Z4zL8CkpKcEnPvGJcb38ZJfOuX92X/BoXkbmvpB0vDey/uQnPxnT58rKynDPPfeM+bknw3tdMOq+Ddv8nfnzeC8n/cY3vjGmkuJlZWX49Kc/Pa5njwXZLlg1f3b3Z7x9/MEPfjDmz1ZUVOALX/jCmD9vwpy7iV4U+16ff69K6f/+7/8+5neUl5fjvvvuG1e73O8+WR9PdqFutme4/36yzxD333//mNo6mTk0L6jMdgnrydp3sn5mG7eTYbxz+NnPfnbMnzfbMlaZ5EWPvNwz24Wk45Xv7373u2P+7LRp0/D1r399XM8fS3vMuXXfSH4yvTuefn7zm98c82crKirwpS99acyfZ3vMr2bbxjsf77Xe3utZ3/nOd8b0/InsixO9sDnbvjjRtfj973//pH/z9Hb2bBirEPPWYd5My9vZBwYG0NbWBiAl4IWFhboV/Y8F7zfBnLDCwkIAqduIh4eH0dfXl/bZgoICCYB5O/Tpvl7ENNo4T0Qikci4lZdzmpubqxt2+/v7054FpC+S09VHzhtvC04kEhlzmZOTk3GbNDeU3Nxcfc9njI6OZtyYfTr76DYCTNli24PBoNYW54//Fw6HMTg4CCB1A3NeXp7m1nRWxqu8vYD7nabcEdFoFOFwGEBqnujNBoNBRCIRAKn+mc/kGJ1OcIzZr5M5FbzNm7qFfS0tLYXbex8aGvJkA/YKbl0aDAYzHOJYLKZ5pBybN5eTgaEs+/3+jJu9T+dadI+32Q7OVTwezzBceat7QUEBOjs7AUA6JhgMpsnF6YRpwADOWmSb3ssI4t9CoZD6Qlk2dam9nd3CwsLCwsLCYozwlPFxW3kno9JpydFiB1JMz+zZswE4TA8A7Ny5E62trQBSVl5NTQ2Ya8RnuT27qYDbA8rWJ5MpoCeSSCTkPdNipyfW2toqL7qoqAgAkJ+fn5WiPxVwW+U+n0/f82teXp6+Ly4uBuBY5fSW6XnNmOGkHOXn58uDpufilhU+/1R6Kqbn4fb0h4eH9T3nrrCwUIxddXU1AKCqqgqAM6+cU3piPT09WT26UwnzvZRHek6RSETMFeWypKREckhwPt999120tLQAcOYUACorKyUDHKdscztVMOlwvtf8Sm+RumZgYEDfs89cu8FgEF1dXQCAo0ePAnA8T/aPLLSb7TxVMJlxjn8gEBCrwd8NDw+LJaf81dTUAADmzZuH6dOnA4DmsqOjI43pBFKsw6lGNsYpJydH37Ov8XhcepNzduLECQApnWQiNzc3Q4+dLkbLBNdiMpnU+jSZLLaVuWCUweHhYekZym9paWnaPsRnnKo9JNvzTYbSrfsHBgbQ09MDIMXq1NXVAQBqa2v1jN7eXn0dGRlJe34gEJiQvrGMj4WFhYWFhcUZA09pErdXG41GMxKU8vPzMTQ0BABpMUp60vQ0aNkVFhbi2LFjABz2BwBmzZqFSy65BEDKkwkGg7KYzdwFL5HNoqWFzfbH43F5IAcPHgTgeNYf//jHAUDe1saNGwEAL7/8sjzPT33qUwCAhoYGsVxHjhwB4IwHvYOptNzdHl8kEpEHwr4WFRVh5cqVAFIe2JEjR9DR0QEgNSeVlZUAgL179+L48eMAHI8TcOaQHpvplZse0FSDfU0mk/IqKJODg4NZ87LoTTJPwvRM6EFTXoHUWPBZ4XA4a8zaa/B9pifP/Cq+NxaLqf2cx+LiYrGuZIP27t2rZ1IGmENRV1enzxFmzsipYrri8bjYEDJWpufPNfnuu+/q74sWLQIAnHPOOQCcudq8eTMA4NlnnwUA7N+/X+uTazc3N/c9E2m9QCKRyEja9fv9+p6Md2Njo2SM87px40a8/vrrAICZM2cCAC677DIAwNy5c9VHrteZM2eKrSRrAqT06Klk0yORiPQCZTcQCIjpIPNx/Phx6UjqFq7JJUuWSK5N9pV7irkXZTts4jXcuUXmXkVZHBoakoySrWtvb8eSJUsAAKtWrQIA7Nu3D4CTuLtt2zYAUOLx8uXLtRb5LHPfmIq1aDKtfH5ubq5+x7WTm5ur9UnZPXz4MA4cOAAgNa98RlFRkdYl95+HH35YTCzZTTPfdzx5v55JtJlQx0kdGRkRLTx37lw1jpNCoRweHhadzoHgpnnVVVfh6quvBgD87Gc/AwBs27ZNA0RllJeXJ4OKYTKvNxY3lR4MBtPCP4CjTN555x0AwPbt2wEACxcuRENDA4DUhvHuu+8CAC699FLU19cDSC3cOXPmSBCokMywoNfUpRneotLhWJrvXbp0KQDgAx/4gBbkrl27AADr169XuIjzxWOsO3bsUFvZ1+Li4owFU15eLgOE/TZP9U0G5ljxvaaRx4VEqrWoqAjnnnsugBS9/NJLL+H5558HkKJfKaehUEi0LTfcpUuX6nvOe0dHhwwQt4L3Cj6fL+MUTzgc1rrk+li0aJH+ToX64osvqk/cNKmII5EIFi9enPa3mpoaGXpcw9FoNGOz9DIx2O/3q92UOfP53PTq6uokR2+88QYARydw7h577DEAwK9+9SsAzobJ8Cw3pDlz5mheGfqMRqNpifuAM4derEczHEN9aiaPs59s5+joqP6Hn9+5c6c2iKuuugoAcOGFFwJwjCKekFywYAEAZz3zGS+//DIAx4h3HzQJBAKe9DFbcjHXQltbm+SJ71++fDmWL18OILXe9uzZIx3EzZWGTUNDg9YU23v06FGNI9d6Tk7OmBJuJwLTMKbjxN8VFxerDdSzubm5Wp+HDh1Sm6hDGxsbAQDz588HkL6PUt5Xr16tdWwmehNe7humwegmGuLxeEaagPk9nfmenh4ZdFxvP/rRjwAA//AP/4C7774bAPD3f//3ABy9RfKD8j9//nyNpRnCfL8+2lCXhYWFhYWFxRmDSTM+tLJGR0fFDtDy9vv9slBpsQ8MDMjjJKuxdu1a/Y7eyKZNmwAATU1NuPfeewEgLTRC5sCk5enl0Io2PcPJwu/3ZxxhzsvLk0fPv+Xl5cnzYp/y8/PFFJCWfu211wAAy5Ytk3X65JNPAnC8LTJkZAc6OjpkZZMqNCn3yYDPjUQiaWEQwGGh6N0zNFBUVISnnnoKAPDII48AADZv3ozPfOYzAFJeGUN9ra2tmmt6cVu2bNE4kkUoLCzMGLt4PO5pOCEQCKi/2ZJV+buqqip5iGQVDh8+LO+CHscHP/hBAM78mGFJwGFZ6JWxr8lkMoP9GIuHMhaYjCS9MHpZpudF7/Hss88WI0Ivs7W1VTJ67bXXAkgxHa+//npGiG9oaEiMEBncwsLCtIRhwBnjybI+5hhxjNn+3t5erRnKX319vdhXtveDH/wg5syZAwB49dVXAQDPPPMMACfMw2R10uZkSgAotBIOhzO8TK9DJbFYTGuQerWkpETv3bJlCwCn/wz7NzU1AXDGmky4W//t3r1b65JMSWFhocaMLPW+ffvSjhYD6WtnMjDZEI4b5/P48eNiK8iS33DDDVqjZAQA4PbbbweQSoFYv349AIftmDVrFoBU/0tKStIOIgDOGPO9ZvjZi3IMZjI2vyfrm5ubq7k1Q8fsI9dba2sr3nrrLQCpECTbbn7P5z7//PN4++2309oRCASyHgSarLxmGx+OdXd3t/Q32VUzkZkh1sHBQXzuc58DkEqB4HprbW2VDuNeWVNToz5zjAoKCtQ/Nwv8XrCMj4WFhYWFhcUZA88YHzM5ixZXSUmJLFsyF2+99Za8FeaCXHvttfK6yNbQ+v3tb3+Lw4edosRkDSKRiLwWMkolJSWyAt3HFscL8wi36UWbXjP7RGublqiZlMi+mEdiH3roIQCpXKY777xTbNFPf/pTAE7+z4c//GEAqVjtsWPHZNmaMeqJJh5mO6bu8/nUFo51bW2t5oLW+9NPP62EQubE5OTkiC1hjJ593bdvn2K5ZJSOHz+uZ/Bd1dXVkh32yzyOORG4/zcejyuezPE0j8aSIThy5Iji65SBBQsWqP3MLyA7ctZZZ4l9YPJoMpnEnj17AKQ89JqaGnnQfJaZZDkZmF6YO+EvNzdXckMGr7a2VvNNRuSKK64QW0Avk3146623NGZM5B4aGpKMcv7z8/Mz2FG/3+9ZcmU4HEZzczOAVP5RT0+PZIZytWfPHrEAZIbz8/OVc0GW46677gKQykMEoOTg2bNna2yee+45AM6azFZh3os8JlNnuZP/c3JyxIQz4by8vBzXXXddWvuXLl0qeaM8/8d//AcA51DBAw88AADYunUrAEcX8XNcf6Ojo9Ld5lxORt+4Szvk5uZqDqgD/u96IQDARRddpPd+8YtfVFsBh2nmcx5//HEAqTlOJpM4++yzAaSY42nTpomtNI/EU8a5Fs0DD+NFtv8xC2ZyPxgaGlK7OLdr164VE0n2taKiQmNPWSD6+/ulx3bv3g3AiRiYeU6Aw9Lzc5xPM0l+PMhWniYUCmns2M9wOKw9wyxdw6gP9UtHR4fWKnUmx+Wf/umfpH+51gsKCnDeeecBSNkHZN6B9EMb73fAaUJSbE4wXxaPxzXo5okg0sNUUA888ICEnAPxq1/9SjTYv/zLvwBIKcznnnsOTzzxBIDUws7NzdUAURlVV1e/Z6Xd8fYvWyVm9oW/O3r0qGi4FStWAHASmbkBkPpftGgRFi5cCCAl/JywgYEBhe3Yv5KSEhl03ExLSkoyQjOToSuz9TEUCmmhkRauqKiQcqDSLSkpURl6tu8nP/mJDFQm2FHB3HfffWozBbKiokKGant7OwBHXjg+hFd9JILBoJ5JJd/b2yuKmOHS+fPna9HSUAiHw5LxH/7whwAguS0qKtKcst+NjY1S1FRcBQUFeh4V0mSNO4J9NSu4cj7b29u10dF46e3tFZVuKkWeaHIn8C5ZskQKlejq6lK/zb9xnOjwRCKRSYedzf83q/oCjryyX5ShQ4cOZYRSfvOb32gdcz3xbzfeeKPGjQnPhw8fFv1OBdze3q4+853cFCY6j+4k22g0mnE6LZFIaC4Y3qEsAU7yPeDoTm6idFaYtLx27VqdluHG8o//+I9y3JYtW6Z3cly4ZieyFmnwmOuQBnh1dXXaoRe2l/2mU7lp0yY5urwaora2VldnsF3f+MY3AKQbwVyfjzzyiAwKymk8Htf4mKGniRiwnHszbQBw1j3lkXLX1dWlfZOO08aNG+Uc8gTezp07NffcM7mPHDhwADt27ACQkuOFCxfqXUxqr62tzThMRGNrvDBDkxwjn8+n+aJDUVRUJPkjzjnnHKVKUL+88847MtoInn4eHh7WGPHzCxculKHMduTl5UlO3fXz3gs21GVhYWFhYWFxxmBCjI9JedGyzsvLkzVGa7CsrExsBpmBtWvXquotveyXXnpJiZRkGkwKkolq9LzKyspE5dJDj8Vi8hDcxwfHi2QyKQ/A9OBoTTM5a9euXWItzOPqrNHDPjc3N4uiI5Pzhz/8AYBTm+C2224DgLQk4g984AMAIBaloKBAlu17VT8eTx/dtVYSiUTGEdZoNKoj62QMvvWtb2kOH3zwQQBOSPJv/uZvAKQ8G1LVixcvVriEIZKKigpZ6EwKPnLkiObfrFA70Xk0wyt8XkFBgfpGzyASiYh+pQc6d+7ctFpSgJOAx5AA54fPf/vtt/VcPmPBggWSYzI+tbW18uIoY+47zsYLN8uQSCQkI+xjS0uLxp6elJlQSbmMxWJi4MgI0HscHh5Ou0OPz+c80qPr6elRuNPdjvHCZAtMep0J8WYSNcOubFtjYyPWrl0LIBXyaW1tFTvLOSebUFBQIIaA8xWJRDS+9JR9Pl8G65pIJCacpG7WQmF/iouLpc/ILs2bN086k6UlVqxYoYtRyeRcdtll+PznPw8glcBN3RKJRDQ31C1btmzBjTfeCCClf2fOnCmWnv2fSHKzqWfYN7NmFPtmJqkzdMowSGlpqdiQj33sYwAc5u4rX/kKgNTFsOzX17/+dbEQN998MwBHt5B9JHsSCATEzJjht4mA8861RVkJBAKSR66TpqYm7ZXcS9avX6+x5z6zZ88eyQDn6pZbblFf33zzTQDA5ZdfDgC49957VbaBzy8uLs442u7z+Sa0Hs0bCMySNVwzZpVw6k6uuwULFig6w7muqanR3k47gfPw7LPPqt3cO1asWKE1S/aqt7d3QqktlvGxsLCwsLCwOGMw4eRmM8bGr7QyaZUFg0EllJ111lkAgEsuuUTx6f379wNwEu5ooTPBl9ZeXl6e2CDGQ4uKisQS0IuNxWLyKMz440ThfkYgEJA3wLbOnj074+6cSCSiwmBkfmbNmpURw+fzd+3aJW+GnnZTU5O8BI5vOBzOKLzn1ZFEM1GTbARZjmg0Ko+Yc9nb24tvfetbABymBwDuvvtueeH0ShlTP3r0qHImyBR95CMfEcvAfJlYLKZ3cIy9OlZqHid3J97OnTtXLA3HmyyX2e9YLKaj4Jwzemcnm2N64fSKuru79T9e3+PF95rJxeZdP/R0yZx2dXUpt4NHog8dOqT5pjdO9mPdunXywvn53t7etOKdgLMGuH7pZU80oRLI9MYLCwvFsLJPsVhMbWOO2bnnnqu/892lpaWSO65TVsA9dOiQclw+8YlPaAy4tk021Mt7ycxn8Pv8/HytRXrFw8PDGgPmemzcuBFPP/00gNT4XH311WLEmXDKsgvr1q2T5825v+222ySnZMP6+vrESJrFRL2AWWGfckI9vmvXLrEmXGsvvvhiRsmPl19+GVdeeWXaWJBd+OlPfyqmz6zeTVbBvLmdOoAMxWT0jc/n0x7E58RiMckbGdSmpia16/777wfgsHnMxaFs1dXVZdwCYO6dbvYPSOkj6q8VK1ZkFPSd6Dz6fD7JBBmt7u5u7VtmoUvmw1EOzWrazGEqLS3VOJC9Irszbdo05Qmdf/75AIALLrhAhw7I7pmVm7lOx4IJh7rM6sWAs2DddQVaWloUHqHxEggElGhH4Vi2bJmE9pe//CUA4EMf+hAAhz6nImO14zlz5mjySA8GAgFNymRLrZv9M+l19osTvGTJEgkAKcaamhoZaDxZsG3bNi2w66+/Xv0CnA2eC4KJsDU1NZpgs/Q43+tFzRfzGVSYZmIf5/X48eOqD0Jj5O2331ZS2l/+5V8CAD760Y9q7ji/NIBXrlyZVosEcEKD3CiJkxmvk00YNb+Px+MyQmjcVVRUqK08IbJhwwYZaaRV+/v7dXLEHero7OzUONLgnT9/vpQSF/jOnTu1GXO9TKaP2frr9/szyrfX19fLMaGR98QTT0j2aCBt375dysdMjAaARx99VEYTjaItW7Zo7KiMSktLPbtkN9scDg8Pp4WiAMfoovJk+PvYsWOqS8NNYt68edoAWbn54YcfBuCEDHjggobVvn37JKemAebldQ5mEr5poHMTY8jp0KFDmos1a9YAcHQsw+h0Ln/zm9/IWKHBQ3l99dVX8Xd/93cAUodLIpGIjEYaAEVFRZIhLy71NENe5klft6PR3t6OO++8E0DK0e3p6dF88xl33HGH2kUDiXO8du1anWIzw2pcz5zbrq6ujGr85jsmAs4f5aKgoEB6k3J38cUXqw4a9UlRUZHmmRXjr7vuOqxbty7tf7l/DAwMyAikHtm+fbsS3NnHhoYGvZ9G5kRhXiJtXnTMuTHDhPw792efz6f55D4eiURklHHNUpdceumlmi/aBoODg3jllVcApMaZe6z5zrE4WTbUZWFhYWFhYXHGwLM6PsFgMO14LgC88MIL8lDo+fb09Mi6/shHPgLA8R5ZAZgeAK1eIEWX8ejhDTfcIPaDXnswGPQk6dcNs06HmeQKOJY2vUbzyN3FF18MIJXAvHPnToUGmOxK2m/WrFlqNz3LV155Rd45Px+NRjU2ZlLyZDxp9//m5OTIajfvlSFDwHYePnwYF1xwAQCor5s2bRIzR6/kb//2bwE4XukLL7wAIMU27N27V+FKUpR+vz/jIkGv+mh6KvQy+K7q6mpRyUwiXLZsmdgNMlg7d+4U+0N2jszY6tWrxS6wdszIyIg8EoZ8RkZG5CGR/ZoMzD6aCZbmRYyAs664PnkMdseOHQrjUaZ7e3vFBJCi5xr/9re/rVAI5dLv94uZ4FovKirSuHgVqmS/2B4m0HMuh4eH9U4yIMPDw5pXMo7Dw8MKbfF3TFSvrq5Wojll8/Dhwwo1cU2+8847mkOTofSCmTQT7vlsytpLL72kRHN6+XfffbdCPmRSHnzwQTE4lGHzkmCyj2RD9u7dqzFhyOuss86SbHBeJwv2zaz2zzVIeZo5c6bWDMels7NTCbxs3zPPPCO2j/NO3XLzzTdrbXHtDg8PK/mda2JgYCCtyr8XcNd3CgaDGm+297e//a1CVgznHDhwQHqDKQPPP/+8yk3wc2RtBgcHpY/Zr6eeekpsChmi/v5+jY+Xd3Wxf/F4XHJCfVFeXq5LrBnZ2LZtmxgthlqXL18uNocywQhCdXW1avux/fv27ZO8cEwDgYD02niO6VvGx8LCwsLCwuKMwYQLGGY7OkYPwryng7E7esMdHR1iTsh6hMNhWYu02mnFNjc3y7tijHDmzJnyENiOsrKyjOqbE0W2Y6nRaFRWJtvd3d2dUUEyEAjIG6NH6fP5FH9mQjet3+uuu07WOWP0ZlVl06OlZeuF5Z7ttnK/3y+vhN5ZKBTK8KxMMK9n06ZN+vtXv/rVtP5v2bJFniet8o0bN4q143i2tbWl5eIA3uRQAEgrT2BWGAUcRoq5VMx5uemmm+R5mh4lPUQyCYzRV1dXiy0jQzlr1izlWtATO3HihOcemJtpiMViGUew9+/frxwcrqNzzjlH7afszZ49O+0WciDFLkQiEa1LMlhNTU1iKimr4XDYs0TYbDk+QKpkAvXAokWLNF9mEjLXEeWIFY+B1NFgJuFv375d80R91d3drRwSrv+RkRG1hd7uZPvrPpIbi8Xk3dMrPn78uGSF/Q6FQpof6t+GhgY9h2wVx6SsrEzJ0PSef/7zn4tN5/wuXLgwo4Al9etkQbkaGhrSunS3F0hVJJ4+fbpYELJP3/jGN5QPwueZhWPJtv/v//6v+uVmfMxkXcrHZJkfd4mQnJwc6U8yd88995zW3a233qq/cV+kzti0aZNYHTJEfNahQ4dUooAyMTIyonxMMrj5+fl6HvuaTY+PBaae4ngVFRWJXePXGTNmqP9ck3v37pX+4e9uuOEGPYf5ecy//Nd//VdFEJi8fsEFFyh3ibq7vr5e+opjM5Y5nPCu4p5gE1xExcXFSlSj8jBPtXDz6OvryzBWmOwWDoeVoMeTNGVlZUpI5CSWl5drIfP9k+0bkK6IOMBU+vn5+QrJUWEWFBTIyGF7ly1bpsVGw4dt3bBhAz760Y8CSE1waWmplJl5hYQXFZvfC8lkUoLIRTIyMqLwD42CmpoaLUiGBObNm6dktH/7t38DANG0S5YswU033QQgdRVAc3OzaodQYAcGBjwzXoH0pGEaUia9zj60trbqvVQmhw8f1iYEHmNrAAAgAElEQVRJw/S2227TYuSYEENDQwoDsX7RihUrZFDRODCrNHtlwLrXYCAQUB/5/l27dsnAZMLhHXfcIWOFSZHt7e1aP9xIePrp97//vS6JpNwvXrxYn+c8mrVvvLjGgeAzR0ZG5DhwXpuamqR4qVcCgYAod9Lrjz/+uMIlhHlVDBN/TaOdm4hZk2gsFyGOFdnmPx6Pa5PnHDU0NGhz/MUvfgHA2TAYqqMh19vbK+OWOoOG4t69e5UYzdDd4cOHtd44roODg54kNZtwy3s0GpWcmmFftoGV4qdNmybdwuTWK6+8UvqVp36YbsC+AqmLW8866yzJKQ1EU069MtTdiMfjWoPUh62trZJB9n/OnDkaF87jxRdfrP6yzQy1J5NJOSs0AJcsWaJ9lmv3xIkTer+7ptlE4A7llZSUyPinYdne3q45pIHe0dEhOaUeamxsVNjdfbpu7ty5Cs/yhGV1dbWcf+7FtbW1IlfGsy/aUJeFhYWFhYXFGYNJxxHM+4HIatB7vuSSS+Rx0Wvs6+vTGX8m1NXU1CjERXqTtGBOTo4sRCZdvvTSS2Jd6I1PmzZNITFSe4B3lnxOTo7axJoTy5cvFwVLim7btm36HGnbwsJCHYUne2WGW0jzmfWPyK7QwjXpa/OovZfHoM0wkMmekXI3PQbONT2qSy65RO2j50Wr/8c//rGYK4bG8vPz1V967a2trWlHsqeij3wmkB5eoIfMo+a/+tWvVHuIbNWdd96p/6XHQVmuqqpSTSP2NT8/XzJJxicQCGQkXE8mgduEmRjLNciwW09PD1avXg0gxdy9+eabmmeGC8wqwhwLJii+9tprYrr4+dmzZ4thMcMWZES8rlXE/lFOucbKysp0DJ93+5WUlIhh3bBhAwBHv5Bp5DiQxaupqVHogeO3e/dufY5et8liecWGuGEeyaVsXnTRRbj00ksBpEIfhw4dUruY+Lxx40bJHVkTysasWbOUKMsDCrfeeqvmkHOeLZ3Bq7VIJBKJjDvXAoGAqk2zzQ0NDXj++ecBpJK0v/a1r2lPYQIz58W8F4rhye3bt2tfIGtiXjbr9TyalY259tnH+vp6sa6UvSeeeEIsDfv45JNPSs9QLvmZp556SswyQ5fl5eUKI3F9HjhwQGucOtsrfQM4jCLTPLhmmpubdYcl5XD58uWaH5Z+aWlp0R7BNrIKd05OjtIjKPNHjhxRu8lWTps2TYzWeHSNZXwsLCwsLCwszhh4dpy9sLAw43b2wsJCWWP8XHNzsxgTHjsNhUJiTOjdMK5+9OhRWYW07J999tmMY/Ll5eWycmlZe5WMBzjMDL0sJmkVFxcr2YpeV15enjxP9nloaEhW+Re+8AUAqRyJ3t5eWcxkD2KxmJgserQdHR1px0DN508U2ax+d1zfjPUz/+XNN98Uq0Xretq0afLA6FHyWPvy5ctViIuYN2+e+mbmPTGHwSwjMBm4q12bVXfJzIRCoYxKwEuXLpVXxnj83LlzFZNmcqJ55JjHL5csWQLAYSGYOEsUFhYqn8HrvIJsd9bQQ1y2bJlkirkO27Zt03q77777ADjxea4tM1kWAD73uc/JWyML29nZmVa1HHBkx10ldrJlCYCUXolEImmF6QBnLpk7yP6vXLkSd999d9rnZs2ahXvuuQdAau7Ixl5++eX6X85zbW2tZMLMHeH7vZJTkzkHHKaX+TlmRV/mUZBJLy4uxl133QUgVdX40KFDYjfIkrN9eXl50rUcr3PPPVcMCVnYnJwcsepesXbmEWjAmTN3snZdXZ3klAxBfn4+HnroIQApGevt7RUbQoaEjGZ9fb2ey/yTlpYWMS9mBXD3gRF34c+Jgn3s7e3VOHOMV65cmZHzWVxcrFylRx99FICTdE5GnWVDyOBWV1drn2EuYl5ent7BsWltbRXrYiZ1TxRuGcjLy5OcMs+1q6tL48qSNStWrFAeIZmqhQsXKu+JOodj8Nhjj0nuud+2tLSIrWN5g0QikbEfmnc0ngyW8bGwsLCwsLA4YzBhxodWI72mnJwcxd1pgZuF+OjJb9q0SYwAveZEIiHrjl42vebt27crx4T5BS0tLWJJ6I3F43FZ2WbcdrJeinkaiO/nSaYXXngh46btWCyGL3/5y2nP+MEPfpD2HLON7e3tOsrPv/X19cnzI8uSTCYzCu+Njo56wmqZHjX7YR7T52kzMh+lpaXYvHkzgJSHum3bNnlSZH7Yr6efflrMB+d86dKlysandz0wMCCGwjx66YWHQjktKytLK4UPOB4y20CP49prr9U803vZu3evPkd20SyWR0/GPBXF/BB6qtOnT8+4h2yyMXd37pdZOp6nPBoaGsSO/n/2vjywrepK/5NkWbZkeU9sZ3V2yELSQAjQAg2BAKUUKEuhDFsHpuu0w8B0usz8OtPOlK7TllJaulPWAi0UKEvYCUsgJAQSEkjIQmJiJ7ZjJZYtL5L1++PN9+nqPREc+zmUyT3/KLGkp3vuPffcc75z7jlEH1etWqX36TW++OKLyr0jj//wD/8AwNmbRBDo3W3btk1ICGW1s7NT3+U6+uFJmwUaySN/s7W1VTqEa33MMccIXWPOwaOPPqq8PKIn7M9VVVWFG2+8EUAuJ2jhwoXSZ5T55uZmoZXmdWg/EDzyVVdXJ51BJPihhx7SfucalpWV4dZbbwWQQ4ai0aiew3VgvsT27du11vxeZWWl5oLoQCqVEmpkdhofSldvkvsGVSaTkS6jDPf19en3mK8Sj8eVl0VEqq2tTWgJzxgiPn/9619VAoDFHdevX689yP0XiUTy2hxwHMO5NevOH+zr65OMcg2mTp2q/UM0Y+HChTjllFMA5No3RKNRoa28ns9bXp/4xCckl9RjRUVFkhXq223btkmXm2VJhpvjYyK61HdEmRobG9Wiiuf4smXLtF48uydPniwEi6grb1jeeeedQvx4jjzzzDPadzx39u7d69Hxg5FR35Kb0+m0ID0e0B0dHbqWTQW7aNEiHX5mAqbbaKFA7NmzR4LIjVBZWZkHcfNz7noFw1FE7qt/paWlWhxuTP4fyAnkhAkTdF2UULGZ3EyeCUsPDAyoaRuf29nZqY1DhRQOh7WZKcDkc7hkNg2kIclQ4969ez0hxMWLF8sooDBns1n9jeEQViLds2ePIGc2DxwYGFC/GoYyJ02a5Al1+VX5l5uioqJC8seN9fzzz0sRUYZKS0s1LpZWmD59up5HZUZjf/HixZJx9uqqqKjQ56iwg8FgXokEYPghBHd/oNraWsHa5KG8vFyKkp+bN2+elBZDl8lkUuvIcNavfvUrPYOGIZNhW1pa5MhwL/b09Ay7ZohJbhkoLi6WQcO5TCQSWjvusbffflvGCpN8d+7cqf6BXDsq57a2NjzwwAMAcs10x4wZo2RbXomPx+OeJrB+JYzSQBw7dqzWi+UxmpqaPFVyOzo6xDcdlFmzZmnM3IOUMbNZLRNrx48f7wlrZTIZT20bsxTDcMgsleEOGaZSKYUzyENdXZ14ZOgnm83KKODFGIZLli9frsOe35s+fbqntEJNTY2nv6PfdXyCwaDn3Hj66adVjoW/u2TJEu078jFlyhTxyMr31F2LFi2SAcuzMJlM6oyg8wLkwIGRCHWZqRA0mmtra2WEs7PBzTffLAfJrL/EM4AhOs5VIpHAddddByAHpGzfvl0lQ8izue85l4PZizbUZcmSJUuWLFk6aGjYoS5SIpFQmIJW28KFCwUjs9jSW2+9JY+M3mgqlVI4ix4ir3h3dXUJ5iRElslkhCrR8ywpKZFF7VfxOyDngZWVlcmzNa9wE30hPJlKpQST0wLduHGj+CcPhHhramrkvdHb3Lt3r6xcejNmZ1zz6vFwiPNEzzcUCsnLp2fxzDPP6Jo2vefLLrtMc0Ar/pVXXhEywrWhN1VfX6/wAhHAFStWCGWg9W4mpflVpNE9Z5lMRnJKDzAajUpmGaYLh8OST3pMkydPVrIse8vR65o3b56gXvKYzWaF+PA3d+7cKe/anXg9VKKs0qNjeA3IeUvr169XQj29yOrqao+3dP755+uaM9eT5QlaW1vzwg+A452SN6IwqVRKMuUnmQXwqCc455WVlUqK5Z6tq6vTv3/2s58BcOSVckkPm/u6ublZSCfDJvF4XF4p9/qoUaPy+su5xzcUcuub4uJiD+IydepUhVPNvk9EgXjtt7u7G0888QSAXAVqrvm0adO0ZynzO3bs0J4l1dbWaj0pz0VFRb6EZLkXe3p6xCP1YmVlpeaRsrljxw7JGEOWfX19QsM5ZzxDFi9enFdRHcjvA8jf7+/vV5iIcjTc1AG3vtmzZ4/2OxE2s+QJw887d+5UKRdGTs4++2ztMzNMBjh7nMgJ1zGZTCrERcSrpKRE+svPYqJmagfRT7MnmRl+A5zUAZ5lLDz53HPPCcFhcUPO0YUXXqjyDEz2Pvzww7WulI2dO3dqL7hD/vsii/hYsmTJkiVLlg4aGjbiQ08xnU7LyqOXW15eLquU3uPq1as95exra2vzvGQghyQcfvjhshQZNzQTGentVFVVefI5hkPuwlaRSEToFT2hk08+WQnP9KbXrFkjz4P5E6NHj1Z3duYT0DqdOXOmYtq80rl9+3bNJb3S3bt3y7L16xq0mdsDOF4Pf4O/n0gkdI2fcz5lyhTFZOmJjRs3TtY7P8ckwl27dgkBYHLw2rVr5alRRmpra+U9+N3rid5eS0uL8nnoKTU0NCjhmZ5xOBzWd+k1z5kzRygQCzEyF2369Ony7Pj8dDqteeJ6l5SUyLuk1zTcJHx6OJzPyspKT3+gRx55RN4sOyBv27ZNyMBFF10EwMmjY7Iox0QvbM6cOUL6mCczb948JTybSC55JA0nB8aNiKXTaXmXlN3u7m6hBvz8ihUrhIJQJ0ycOFFJvVxLeo+NjY2eth5vv/225pV6ra6uzlO63+8ilB0dHfpdIlKTJ0/GySefDCCnTxOJhKev39KlS+Xxf+5znwOQQxaeffZZ6SLO1/PPP688IqKF0WjUg2r5lYRPOTFzGTmWQCAgfUBd0NbWpvXmlfTRo0crF4Z7kHv8mGOOke6h3kmlUtrvfK+5uVm/b+aY+qF7+LxwOOzJxRw/frzOATP5mqgk1zsajarFDxEkvt5///3in5dOzPOWaFhRUZFv+ZIAPGd3IBDQfJLPVCollIlnwqRJk3RussDoCy+8IN1BeaVsjBkzRonOzB1qaGjQbzCXae/eveKLZ1GhXptuGrKFYBo85v+B3IESDocFvTG5sLm5WTdhCCfX1tbqcOFBzwVMpVJKljX7zTAJlhvCz2qUgFfZ9vf3SyB5wK1Zs0a/SeOsrq7Oo5SDwaAMNIbBCNXv3LlTBwsVcVlZmUIU5LOvr0+HyXBuVpjkNu7S6bQEisJcX1+vysUc84wZMySMPCBmzZqVd8PGfO3o6FDNCSrTyZMna0NSXioqKjyKaLhkVlAFHKOShqmpHLimTGA1v8PP9/T0eKoUU4GNGTNGRrB5y4HzxIO3u7tbY6LyGG6SuvtA6e7u1gHG0M3atWs9SmPp0qWqPcSxrF69WmvPGxSXXXYZAEcmGIKmYTVlyhQdUIXCBX7C6+bNPB7yVMTJZFKKj2O7//77VSeEIY9NmzYpaZbhV67XunXrxDtls6SkRMaeGS4l+RWa5XM49vb2do3LrG1G/ch1KCkp0R5kQ84pU6bgiiuuAJALjVxzzTV6Pm8P0bB68sknPXVvampqNJ9cz+HezHPfOuzt7dWcmvPH+aWuWLJkifYdnYp169aJb8o1ZT4UCknPUu8ceuihckL43K6uLhlGfvfsMi/FcP5Mw4tnCcc8ceJEnHjiiQByt9TWrl2r21xMXGdofcOGDZ4b0NFoVAACZaazs1N70I/egO5nlZaWekKyHR0dMlC5XvF4XE4YHfy+vj51MqCjfe+99wJw9DTDXzTsOjs7ZexRbmKxmORyf3rL2VCXJUuWLFmyZOmgoWF3ZzcTZN2eXyaTkaVOK+zwww+XJ0kLcdmyZR5PmvBzJBLJq90A5Fu2JhzrR4jLzZ/pEdADo9W5atWqvGuDgGOd0stgiKinp0fJz+4k7jFjxshiZQJ0b29vXuVPIB+C9buSKucwmUxqnPSoq6qqBP8Tqty8ebO8ZoauJkyYoMQzJufRe25paZHHQki7tLTUk+yYTqd98UpMoofC+d6zZ4945FX8qqoqoXSEaIFcYjC/e9hhhymBln8zkRx6LSYKwL1AHs0+Wn73B+JvNDc3a3wM3R122GHy/hn+mTp1qqB2VkVfuXKl4Gnyw+e+9dZbQrW4tgMDA54E0XQ6rd/386KBicIQjeD+SCaTnsrUEydOlOwSkY3H4wr78PMMlaxatSoP8QAceSVqRrSlu7vbk0jpVxiIc7hnzx7pO/MSCBNgKaezZs2SDNKTLikpkY5lxWOiQZdddpn0Kb3x7u5uyQlfS0pKpBf8IncS/ujRo4WIUrd0dHTkdfQGnPWhbmGU4AMf+IDQvGuvvRZAriLw+vXrFSIikjtt2jSdLWY9NL+rp7vTLYqLi7WmXM/q6mpFOIjotLS0aO6J1rS2tqrUCS9dEIU2UV2zZhN/36xO7Uaz/LjOTrnv6+vTWcU92djYKHSLstvc3CzUld3n58+frzX+85//DCDXB/Okk05SZIjj3bBhg3QNz38T8dkfsoiPJUuWLFmyZOmgoWFDJGZ8z209Z7NZWa/0rhoaGmTxM2envb09730ghySY1TXpeXV3d8sKZA6Mn7kEQH7eC+CgGBw3f6u5uVneIi3c0tJSxZJpCY8ePVr80bOh5T5x4kTFdMnfjh079Bv0iEyr1i+kwN0fqKqqytMfZfPmzfKazevSzOeh5xmJRITSkcjPrFmz9G+iQdlsVta7u7vuSPDIsVdVVWnu+bt79+5V9+OLL74YgOMN33DDDQBysvjKK69Ixt39jiKRiLwQUk9Pj+eacCaT8QUFKUTkK5FIyNOl/FZUVCiBleO84oorFEdn8cWHHnooDx0DcpWDe3p6JNNc987OTs2JubZ+8uiWBVPX0MsMBoNKuObnzz33XMkd9VB7e7vyY6h/6HUGg0F50dQrVVVV2oPckyUlJZ5eZH7Jq3nVm/k+JuJmXm0HnMrh7IHEsgPm9W+Ok8jeggUL8rx1wNmn5JFJpmZPO79REc5jVVWVkEMibY2NjRoLc0J6e3uFkHBM0WhU68dcF+bNxONxoefcf5FIJK/iPV/3Jy9kf4iISygU0nxTtqqqqqQ/zEKT7G3IizLV1dUqGMoyEkSyiouLNRdmVMKdM1VUVJRX2M8v4hpmMhmtl1mlnXLE35w5c6Z0LNdp06ZNym9lL7ILLrgAgCMHRNxZEDYQCGhe+fxIJKK/7U+enW91fMwF5uQDOUicQrds2TIlaHFSFi1aJHidQsyDqqmpyZNAHY1GPQlVI0VmWIkLzI3T0NCgA4A3vqZNmyaolgdNMBgURE2FysUPhUKCQs3bOe75zWazI8armXRIfihYoVBIG8w0lJiURkO1q6tL60qjiDx2dnYq0dlMwPW7CeK+yMz8ZxiA8HlpaakSWDkX48ePF/TMWwi/+93vlGhHojIrLS2VUWvOp3tt/VawgDcxM5lM6t9U/Lt27VIdJrY7uOWWW3SAmjWFuKY0Grgn29vbxQ8N8XQ67TF4R8qwM/k0jRDA4Zlyyr1266235hl+gHOokD9+l3tyzpw5ckL4/FQqJTkl+ZV4b5J7b0ciEY2FOrS/v18OFA/JxsZGKX7qpzlz5qhWCg0AGhZlZWXST+7bMOY4RlKvmuEg/ra5FgzFkf+9e/dKt1Dvv/766zrw2bCVIcxAIKC5oHNj7kU/GucOlkcz+ZfyWVtbq/OO4bmOjg6FUlnVf+XKleKJNW3MM4KybV6g4Dnrd7K2my+zYjnXga/mTTJzP1GPcn/ecccdqk/07W9/G0DOoE+lUjJ8GV4vKSmRrJtVqIeyhjbUZcmSJUuWLFk6aMi3Xl2BQEBWID2kvr6+vFAR4MBbtLxpDQYCAb3PhGAmKHZ1dcm7NFGeQhDlSCAGJn/uJEsTqmXyZFFRUR4iBDgWOWE7es8cfygUEhpCaDsQCOTVSTB/cyTIrM1AS5pzHg6HPT1e2traND56VLt27ZLnT8ufaEMoFFJSt7lG7nDBSJLpZbo9hNLSUvHByrBNTU1Kfmatifr6enkcRHfosSaTSY83ks1mPT3oRpL4G6FQSHNKT7qhoUE95EzP0yyXADhyRpkmPwzjdnV1yaPkvjYvFYyUl+kmE1Eyky3JK8MCY8eO1ZyYV/TdTRsZMjEbjfI9s04O5dWsou43mfucYzcTOYmiktauXavx873p06crlEJ0hzp38+bNBRFmdzV4v+rZFCJTd7v7DnZ1dYlvM9Hb3deuUD9D8pxOp/VcymY6nZbsUneNFDJpknlhg/pw69atCq+aV7G5juSjrKxMc8HPc++aIR532Q0+z3z1m8xzifvJXDd3GY/6+nqtCc+7uXPnCnXnhSHqSzONxDz/3Q1Jh9pw1SI+lixZsmTJkqWDhny7/216B6YXRsuMnuWUKVPkXRARicVisu74XXpXZgXdff3uSMZr+fxC1ibj0bS6k8mkEC9awuFw2ONlkkzvkdZuJBLx/brsYMhEmshjKBTSetEDM/N+zIRWoh/kx8wlcCMfZpLvgUB8THKjaH19fXnIFeCMnZ4GPcqysjJ5WfRA6WWZyfWmB+RG6g40r/z9yspK7UFzT7rzt0yUildRzWKl7pIR2Wx2xK7nvxOZydMmauhOxo3H45JJM0+G3zUT0wFnL5I/vpdKpTwVzg8EFUJ9s9ms5I35Wnv27MkrPQE4iDvLg3APmvJJ3vjc/v7+gus60utp/oZZHsW9R0zkw0waNscP5JAS83OFzocDgfSQzP1k/i7PAa6ZeVay9Mchhxzyjv38amtrPX/LZDIFUdeRXEczEkKdWFRUJETcTHKmnPK9eDyuf1NeiWyl02mtq5mo71fBUP8K38BbmRPwJq7GYjFPYjKNBvNz5jMLCap7MQ9kKIHjDwQCCsmZCZ4UdCYUmjy5laiZCG7CzH7fUhssuQXKVESmEcZxF5p3rqepaAp97kAbAST33GYyGSlNs9o2jVpz7O4D11S+7qqm7u8eSCrU9NJNAwMDea00AGfs7tsvpvJ181jo8DoQ5A51mwrYbNBoyizgrC/XmPuYr6acmvv0vZDTQnLT39+vMIH5Oa4tv9PR0ZEX9gHy97Xb+QLgMbIOFLlDMuYlDvNCgNshNqudc8xmSx/3mpnPONDr6f69VCqlPWbe+iRP1DtmEr9bjsPhsGcPvFd6p1A4312V3qztxRuWQG6v0qk2b6i5DdVCjuRQyYa6LFmyZMmSJUsHDQX2x/oNBAKtAN4aueGMGE3MZrOj3u1D72P+gP/7PA6KP8Dy+DdOVk7/lyyPf9Nkefxf+r/I334ZPpYsWbJkyZIlS+9nsqEuS5YsWbJkydJBQ9bwsWTJkiVLliwdNGQNH0uWLFmyZMnSQUPW8LFkyZIlS5YsHTRkDR9LlixZsmTJ0kFD1vCxZMmSJUuWLB00ZA0fS5YsWbJkydJBQ/vVsiIajWbZW+P9RHv37kV3d/e71vAuKyvLsnfK+42ampraBlOMKhqNZtnt+f1Ee/bsGdQaAkAsFsuyXcj7iRKJBLq6ugbFY1lZWZZd099PtHv3biSTyXflMRaLvS/3YkdHx6DXsLS09H27F1Op1KD34v/1dYzFYu/bvTgYHktLS9+35/47yel+GT7l5eW45JJLhj2gQr1F3P2g2JPF7Ktk9uVx074KMd54442DGldVVRWuuuqqQX3WTSZPhRqMuj/nN1155ZWDqqxZUVGBSy+9dL+eXWhuCzXPK9RbZV/P3J9+a7///e8HPd7Kykp8+tOfHvTn3eN6p/GY/X7cnzffG+oa33DDDYP+bHV1Na6++ur9en6hddzXmM1eSUB+k86h8viDH/xgUJ+rqqrCl770pf169r50wL76iRVa86Hy95Of/GTQn62oqMDFF188pN8pRIV4c+uid5LTQr2t3on+8Ic/DHpMVVVV+MIXvjDoz78Tudev0Nj97Ad43XXXDfqz1dXVuPLKK4f0O4XGvq+9aPYbK8Sb+7v74v9HP/rRoMZYXl6OCy+8cFCfHSoNpt9fIf27L7rlllve8T1fm5QWIrciMZvQmR3ASWxSxg7nmUxGnZX5Gg6H1STzQHVnfycqdDi4hdls6klFZDYyZSPJZDKpz7ifu7+L7ie517BQo7hMJiMeyRvXMhAIoLS0FECuWebAwICnm/Z71dCT43GPpVDnaHfTR9PI4+fJl/t9Puu95NOkdDrt4TsSiWg/cq1Gjx4NwOmmzGa8fOU+Bd57Ht1NKM3O2GxgGQgEPI0xyWddXZ10DJtHdnV1/U3Ip5vIV3Fxsac7dn9/v/5NWeTnzeaeZsNLPuO9ao5ciExHyr0GZpNOd2f5oqIi6SK+ptPp96wR62AonU5Lp5iNSd0GD/kJhUJ5uhTI717+t8LjvhqoBoNB7Us21TX547ryfIzFYp5zcahnos3xsWTJkiVLliwdNDQiiI9p0blRnUgkolb0sVhM3yE6sG3bNgDAG2+8oe/NmjVLzwPyrTzTQnT//kiRiYDw37S++/v7xR95HxgY0DjJJ8dbUlKiz/MZvb29Hg9tYGBg2FbuYKgQ5M1xkUKhkKxwepS9vb1CAbiGPT09+g55NJEFxo2JBpne+IHwWEzviPPNv2UyGXkjpP7+fo2LyADnpqioSDxybXt7exWyPdCeWKGQnBt1bG1tlTyaCAJzMubPnw8AmDp1KgBnPbds2QIAaGpqAuDsP8oC1/PdYHs/aF8hK752dnaiq6sLQA7x6e3txe7duwHk9A/zwaqrq9He3g4gJ7v9/f3ax25v0/3vA0EmYgM4/HAM9JoTiYTWmvdvv2AAACAASURBVPJJ2TS/TzktLS2VPFMOQqHQAUF/Cs2fe8+kUim9x5yooqIijdmN5EQiEc0F1yydTnvkw/z3SOpUdwpAMBj06PJ0Oi2ZM88G9zi516LRqOdMSSaTklWuu4nmHUgqhK65UUgzXOdGZgcGBsC8KZ4PJSUl+i5lhHOwv2QRH0uWLFmyZMnSQUO+IT5mXJ9Wp5nbUVNTo89OnDgRQD7iw1wBemPMdxk9ejSmTJkCALIA3377bVmGpgfj/n2/yW2lmwgAx1FWViarnN5GIpHA5s2bAeQs4XHjxgEA1q5dK0/gyCOPBABMnjxZ80EUpaenRx7BSHrRHIvpDdLzoLVdXl6uf9Nbbmpq0rzQExs/fjwAYNeuXWhubgaQ80pbW1uFJPC1urpazx2qJT8YHt05SwMDA0IG6F12d3fLC6F3EQ6HMWbMGAA5z2vHjh0AgPr6ejQ0NAAAGhsbAThyumnTprznBgIB8ehG0kaS0um0eCRa09bWpn1EtCYajerfzHNpbW0F4Mgx9yVRvVQqJb6j0SgAZ25GEp008wRNhJByyveqqqq0L2trawE4eoVj53sf/vCHNf6XXnoJgLN2AHDooYdK7/DzXV1d8rLdCIxfZOb0uS98ADkPORKJIJFIAMjpTjN3i2vJcaZSKaEm1M2JREL7kzJZXV2t71LWR4Lce7G/v186z5Q/jplzEovFtAbcT8xF27x5M1577bW83zniiCPEL/dBT09PXsL+SJCpq6lTi4qKtFfMnFYzKkLauXMngJyePeywwwA4+nH58uUAgNdff12fr6+vB5BDxioqKjQ/Bwr5KSoq0hnM+W1ra5MeoRx3d3frnKN+nD59OgCHT0Z9KJP19fWoq6sDkDtHdu/eLR22P7pm2BaC+WNkiK9mMhKVbU9PD7Zv3+78+P9OTmNjoxQNF+zUU08F4AgzoXcKSWtrq4SECz0wMCClzMkulIQ7VP4ymYwWx9ws/A2OLZFIYNKkSeIVAF5++WUZOueffz6AnCL6wQ9+oMORPC1cuBAtLS0AkJekxw1hJr/5QWaCK3njIVJSUpInvIBz2HMzrV+/HgDQ3t4uA4YHCRXYkiVLNCe8SXD77bdrvfi90aNHSzY4Jr8OFjNB2R0y7erqkjLk70YiEYVY+ZrNZvU5rg/5WrlypTYxD6JsNivjnkq8uLjYc9PGvBnnB5khQ65dIpHQuOLxOADg6KOPxsyZMwHkDsG7775bMvfII48AgA6RQw45BJ/73OcA5AyJFStWeAy+4uJihYy4L/zk0YTIuRei0ajGxEOit7c3z6ADnHVYt24dgJzzwTWMx+P485//DCBn+MybNw8nnXRSHi+vv/66jCfOqd9raJIZXqVO4Rpms1npJRpoJ510ktaCBwUPndWrV+u7pNWrV2PZsmUAcjo5Fot5btaGQiFfD89gMCg9wvlLpVLSCzwzRo8ejZNPPhlAbm0feugh3H///QCAadOmAQCuuOIKAEBDQ4N0Kh2TSCSi73IP9/X1efgJBoO+GOtmugf3OXVqRUWF/r1161YAjv4kOMDDf+PGjXjmmWcAOHsVyD9vaehyD9fW1kouqZ+AnPFLA8JvA6iQA0eeyd/OnTu1Pz/2sY8BABYtWqR9RuONzxo/frxk4pprrgHgnCMXXXQRgBx4kkwmPYbPYPizoS5LlixZsmTJ0kFDviE+mUxG3giRiZ6eHln0tEDXrFkjL37hwoUAHE+CoSASLfVkMokJEyYAyIXGSktLhRLQmt29e7fnCuM71ToYCn/ZbNaDPpSUlIhXeoPRaDQP0gSAKVOmyHt6+eWXAeS8jrFjxyqJlJ/ZsGGD+CcvZWVlspg5D35dGzbDdbS4TZibCa1vvvmm+J4zZw4A4AMf+ID4p1dGePZrX/saAAdmfuihhwAA5557rj7zwQ9+EACwYMECAA6iZHrrQH55AD94DIfDBRFBM+wKOF4Z0UR6LQ888IC8LCJ3pofsTrxrbm7WPNIDDwaDep/y1NPT4wuPZmiEMkjULRAIYPLkyQByKOm8efP03ZUrVwJwZHX27Nl6DgA88cQTAByvnN41vdK1a9fKUyXy09HR4Uno9ENWTdSOVAiNoPeYSqUkp/QQd+zYIf7fesspfXXbbbcBcDxmrhORnLfffltoHd976623tIaco0wm46snbSYW8zf6+vo0FvIwZswYT5rAvffeizVr1gDIoUDUHatWrZIc/Mu//AuAHEILOLoHcJAV7glT75mJucPlLRQKCYnj3olEIkItOMdVVVWYMWMGgJwsvvLKK9I9jAiY5QmIgvC3UqmUECSiXx0dHfp9EwXzA0k3UV3q1FGjnPqyY8eO1b40k+mPOuooABCv3d3d4pGoHuVy06ZNGvtpp50GwEGFbr31VgDAww8/DMA5Z9zr6EfiuplWYqZ+AM5e4PNpE0ycOFHjoIwtW7ZMemfXrl0AcikxJ510ks4FpoA0NzdLx1Dmt2/fLoSQ3zVD7e9EFvGxZMmSJUuWLB00NCTEx/S4zGvXtO74fmNjo7wLWtFr1qzBBRdcAAA455xzADieNBGcJUuWAACuv/56AMCLL76I008/HQDw1FNPAQCefPJJeZz0ZMxETdOyHQqZ3qnpidPCpuU6evRo/SatzkMOOUQ8r1q1CoCDbnAs9FgefPBBAMCVV16p+XjssccAOFY9PSAmW/b09Oj3zZixWSxvqDzyefF4XPNJD6izs1PxcvJ47rnnCq276667ADhrwvwsriHjsVu3blWclshfSUmJLHn+1ooVK4R00XuIRCK+JsgODAxo/QqVJTATSBlf5/hisZgQqUMPPRRAzsvu6uqS58U1+cMf/qDPESkBct6N6e0NB510r2MwGNS+JOIUDAaFFtDzfeCBB5TUyt9ub2/HJz7xCQCQB0o5LioqUl4F0ZINGzYo4dtMgqZnSsRyMF7Yu5FZ4I37zrwaS9l68sknATgeM/9GzzIWi0nXEK0jGpnJZHDzzTcDyF3lv/7663HttdcCyCE+gUBAc0hdV1FRMeRk9XeqFk4ezWRcygz53rhxo/Qu80b6+vqEkjM/jRX3E4kEzjrrLADAs88+C8DJp6Bcn3DCCXo+UQkzd3KoCGwgEND6cexlZWWeZNyXX35ZskOdOXbsWNxzzz0AcnJ3++23a35YofeBBx4A4Mgw5Z4IgZk0zf1n/oZJw9E3hYq8mvlLgHNWMZeRcllcXOy5vv/qq68K/aH+IF979uzBxo0bAeTWsba2Nq/wrzkek1cTpRkq8VnpdFp7nLI5atQoPZ+ocjKZVMSAiM+FF16Ir371qwCgqAJzCJ999lnpU6J38XhcCew8K1988UVPqYYxY8a867m434YPb/64E0TT6bQGwETJadOmaUNR6OLxuOC7z3zmMwCcmj1nnHEGgNyNoNtvvx2AY1wwrMANCEChMYaatm3bpkWngcBn7S9/5iFkvlLoCFnW1dUp85zwejKZVMY55+Gkk07CRz/6UQC5tgRUyAsXLsSLL74IAPjWt74FwAkREb7lBgmHw55bFkNNxKPR474FZwoWkyLfeustHd6c376+Pjz66KMAgDvvvBOAAxtTsD/5yU8CyCniJUuW6N8MK5SXl4tvKu6nnnpK/+aNsPr6+iFDz+bccKOGw2GNxbzBxcObhsCbb74pvi+//HIAwNKlS/MSvAEoGfauu+4SNGsmZzIxljLZ0dEhxUsjaziJseY6moqNsk9lEAgE9D7nPRQK4b//+78BOEqWfHPP0kBkuGj8+PE6hF955RUADixPOeee7O7ulkxxrodj9Lj5C4VCebdWyCcPwg996EP6HPcljZ1kMqnwz5lnngkgd6jcfffdUt50rMaNGyfng3vWvLTBPTkcJ6vQ/81qxTzEWlpaPDWTGhoa8pwuwNEPlEsejnxGZ2en1pPyv3TpUq0r9XBDQ4PWn/JKI39/yZRRIJfAWlVVJUfLNPIYluTarl+/Hr/+9a8BQK0hbr75Zq0LdQUN0+nTp3ue29raKpmkUdjb2yunhvMz1JDlO32nuLhYe9C8OMKDmQZ2W1ubHPsXXngBAHDKKadIN9BAog4ePXq0dBb38xtvvKHfIo/jx4/3pGNkMplhJ+ObRhrn2NSnNLi5Do8//jjcPdueeOIJgRp0mjgf2WxWKRN0vGfMmCG9QwAhkUhg7NixAHIG9WBuddtQlyVLlixZsmTpoKH9RnzoObo9FfPaHi320tJSeYF8Pfvss3HHHXcAyEHSp512msIjzz//PIAcvFtfX48//elPAHIhh9GjR8u6ZC2D5uZmwabD8TLpnZh9bID8q97mNegVK1YAyK/TQuSDr8cff7ySDZkoa3qqvDZMdGfHjh26vkgvLpVKyXKnh21WNN1fHk1yV0oFctevU6mUB6K+5557lJjMBMkf/vCHQsK4XkRF5s+fLy+PKMq8efPkXXMNd+3aJS/Gj6uXhdCQQCCgeeP67NixQzJDZKatrU0eCq8/33PPPZJBjvPYY48F4HjghNXvvfdeAA6SwOcyYXPLli3yvMxKwG6veLCUzWY95Q3S6bRQAD6zsrJSfyOacdVVV0mmuD+nTJkiD47hWBO2pse1aNEiAE64mt4o19Osb2VC/0OF192XBaLRqKfScCaT0f6njLW3t4s/orDLly/H//zP/wDIXX8mlL5r1y7853/+J4Dc9eHa2lohztx3b731luaI4xgqKkldU2i+3NXOy8vLPYjsmjVr5L0TqWtoaBDSQ8+Y4YUFCxYImSQy9uCDDwrxY9iiqKgoL/kewJBr3rhLD/A5e/fulU7htWYAOOaYYwDkknyvv/56/PjHPwaQ04dXXXWVkDpGEKhvysvLddFi6dKlAJxzhHwQNclms/qbuzr3UHg09y/XpLe3V/uO/I8ePVoyR1Stvb1dZwQjIRMmTBDK+N3vfhdAbt998pOflEwT3Vu9erXmgrXvSkpK8mrBAfnh/KGSeRZyHDyzq6urtT+ee+45AE7IlWEvnoEdHR1qWuyO1pxyyinSmZyjeDyu9aT+bWxs1B40OwC8G1nEx5IlS5YsWbJ00NCwr7Ob11Zp5ZrXK9euXQsgl2QWi8XkzX/7298G4Fj29EhonX7xi18E4MT+fvrTnwLIWXmLFy9WrgW99oGBAU+cfThXaAtdxzW74AIOKsD4Iq3NRYsW4emnn87722uvvaaxERWht5JKpWSJMxl42rRpinmSz1GjRnl+f7jkzmPavXu3p7dRXV2dvGYiH+FwGBdffDGAnKd02223yfOnV/bXv/4VADB37lx54UxonzlzprwB5lwUFxcrNu1Hboi5/vRe0+m00CzGkKPRqKciaHFxsXIbKK9tbW3iY+7cuQByOUHV1dX6LpG7+fPn62+rV6/W8+m105MZaoI6eXQXK+zq6tLvch0POeQQzQG9qh/+8Ifykrl25557rgd94Nw8//zzkgV6WU1NTZonImkm+luoe/3+krubutkDjfPf2dmpSwXM+Xj22We1t5jQe+eddwrxIKLAPXnUUUdp3pjQff755ysJ3yzW6WeR1GAw6OlRVwgFSqfT2m9MAN65c6dKZHB9Z8+eLX6J7pGvGTNm5CWmAg5Cz+dRd2/evFnfMYtQDmc/cs64Jj09PUIauRfr6+u1jsyfnDZtGj772c8CAP71X/8VgIOa8IygLDJ/8uSTT1ZO0N133w3AWUeitfy8mffjLio6FDL3InVqMpnU3JLvUaNGSedRF7S1temMpPw2Nzfj8ccfB5BDtah3brjhBl0w4eu0adOkq8ycLuo7P84Nd0kJ8/lm/hmT/5mHdcIJJwiR5Bx3dXVp73G8zD/r7e1VJOD4448H4OhJ6pojjjgCgGMTEBlyJ3bvi4Zt+JgLTaOFiXdr167VAcbqqL29vbotwsSnt99+W5VDmRhLqPInP/mJDAkempFIRL/LcEQ4HNbE+1FPw538ZVaG5kEwduxYCSkPmPr6ei0UN9/evXsF37rrGzQ1NeHSSy8FkAsVFBcXaz4oaL29vb5VajafS944ThOGBhzIlJuJimP79u2C0mko9ff3KzGSoU7C7HV1dVpDGnyrV6+W4mXiaSKREI9+tHMoVPY/k8nod2mY1tXVCRo2b5XxO4Sbjz76aMkbb5nwvcrKSils8njooYcqhMDbKKFQSOEEs/rucAx0tzLq6+vLa18AOKFVfo63QDZs2KB9+fnPf15zQmOb+5g3Lp544gndtGAi6YMPPijomoaEWfXXz5oonLdMJiP5IJ/mTR6u4dq1axU2oEI977zzVLGZe5Hhu8MPP1zrZDZNpsJmOMasU2I29Rwuf0DucDLL/pNisZjCedyfkyZNkh7lGGbPnq2k+ptuuglAzlDq7u6W7J544okAnARu6k4+N5lMaizucPFwibqyu7tbskNnoba2VpXCqQMnTZqkEAfXZ9GiRTK0f/vb3wLI6dTGxkaFm2lMzJkzR/JPgyoej2t/+FXl311xPpVK5c094Bh5HDuNMPO2KS+AxGIxhYforNAg/973vqfbwP/xH/8BwJF76mMCAnV1dXl17YbLq7tmj1nXicbc5MmTlXBNm2D37t2aB9bbOe+88yR3fI+G4J///Gc9j2u4bt06GcgM+Y0fP16GF18HQzbUZcmSJUuWLFk6aGjIiA+tPBO+pEdA6y0ajcpS5ZW0trY2JXbRer322muFojBZlF5JNpvFP//zPwPIeaBdXV2y/BkmqKqq0r+Ha70XquNj1oHg61FHHSWPnwnKxx9/vFCBxYsXA8i/XkcIkAjIkiVL5MUx3Ldy5cq8qqWAM78mQuAe53CI3klvb6+8fVrPoVBIsCKt85deegn/9m//BiCXGHrWWWcp4ZnhTV5VvOuuu5Qoy/WdMWOGp5KweZXU7+aWZrI6/835pFwBOc9zxowZkknCsVu3bpUcc905dnMtiIbs2bPH4+Ukk0nNt188ukOWPT09Qlo59ng8Lo+YSNdnP/tZrRlRkscee0zhPKKZRHyOPfZY8cYw5cDAgKdXV29vrychdrhX9s1nFRUV5V0mAPKbpXIeSktLhWD84Q9/AOAkMBMaZ+iWa/6tb31LPPCSxa5du4SQEakIBAKexp0mCuQXUY8RFTBrFfG9+fPna66vvvpqAA4qwtAqLxow5NXZ2am1ph4bP368UCPOcTKZFKrmVzNdNzKZTCblwZtzRx3JZN9UKqXvch9NnDjRU7GXIczzzz9fl04YGpo9e7ZqNPF7tbW10s1m2YfhkHlhga/ueUwkEiqzQP1xxhlnqJ4U52fevHnSlwyz8rr3aaedJr3FZy1dulR/I7qUzWZ1LhJRGm7IEkDeWeuuTD1hwgQhTvwds2ksx3HUUUcJreOFJ7OnHmWCEYRHH33U07Q1HA57QrcmCv5OZBEfS5YsWbJkydJBQ0NCfApd945EIrK4GGcMBoOK2RHd2bRpk65y00ObN2+erEBezaNH97nPfU7XLokCNTc3yypmvL6rq0seGd8bTCGjd+KPZMZqyRet6VAoJM+KiEYgEFCOD71Cs5KluxtxZ2enClcxHl9aWiqvm9asGT8uNM7hkDlP9IY4/729vUogpWXf0NAgL4Pr+/rrr8uDJuLDvJnFixcrCZy5QZs2bRKaZSZ6c47NiuB+kJmsTsTDzB1h0TB6zzU1NULdmFBXVlamuDPXh954cXFxXmFAwEm8I6pFmdm+fbsnWXeocuomU8Y4Lu617u5uefVMhrzkkkuEPLJ4Zmdnp/YUkQHyMH/+fMkHeZ02bZqQMXreXV1dSs7nevrBl+lNkz9eeAgEAtInJjLL/B2OY/bs2Vpj7sXjjjsOgCPr/Bvnrb29XaiR2V2be5vyOZwEdXMfUxZYJRnIz91hrgtRqgsvvFBoM/Xfzp07hZYQ1WQ/riOPPFLX+TlffX194sfMo+K//UZ8zLIL/BvXccyYMUJJqRc+9KEPCclgTlA2m9We4n7m3L300ktCHP7+7/8egJMvRL3EeTKjBEO9qm+SmcDP5xYXF2ueiYhs375dupLz/vbbbwuJNHXFL37xCz0HAD7+8Y8DAL7+9a8rf5C5pJMnT/Z0T9izZ49kwF35fyjkvrRQXFysteGeTCQS4oGIciQSEUpMtOaaa65RvtVHPvIRAE5OL+CsOfcW56Wvr0+ILJGfSCTi2ScjmtzsTngzK+JycmKxmJQtIccJEyYIvjv77LMBOMJJKIz3+s3GfLxxwlDQjh07lCBNJd3c3KzkYD+TgEnpdFoHATfa9u3btXBUlJWVlVooCu3s2bPxd3/3dwCgVyqVWbNmCYan8XfCCSfIKKAS6OzszFOKw6VCcGA2m9Xc0fDZsWOHbmfx98866yx86UtfApCr+Lt69WoJPkN8/P+xxx4rxUuFtGzZsrzbcYBzsJjVRUeCYrGY1opG2Nq1a6UUeAhu2bJFIQ4acIcddpjWiAaAqXQ5nybMzBtuJl+U0+FWT3WT2cqERgiNgGg0qjHz0Lz++uuVgM61+Pd//3cpbd4WIr3wwgsyAg477DC9ms4B4CQ58rfMufCLioqKpDy5lmVlZQoDcS3NCtY8WM866ywdIlwbyuSmTZvEH52tTCYjY8M0wgu1BPCDzEr43Ps0tuPxuNaYjsfNN9+sW2e8/bpgwQI5Ygxx0YhYtWqVdCbD2Rs3bvTo7pKSEs8hOpxQXqGwvHlomq0rqGc49jPOOEOhHq7xxo0b9R3KOJ3r5cuXa35oAD799NMKUzNcVFFR4Qmj+qV3+NySkhLPDa54PK515ntNTU26HEDZbm5uVrNRt+GTSCTwl7/8BUCuLcnHPvYxhQk5X2aYcCQoFAp5mjO//fbb2iu81JNIJNSgmo5Ub2+vdCzngQ5VLBaTzNLxnjdvnvjimRGLxfYrqZlkQ12WLFmyZMmSpYOGho2x00OoqKiQ1UavKZVKyfPk5x5++GFVR/3Od74DwLkmTM+MIRF6Jdu2bRMsSC9y7NixeWEXEi1/M7FsuNYun9Xd3S24nGjN2rVrZcWzzsSZZ54peJ0hgMmTJ+u79Mpmz54NwJkrWrZsEHjccccJSSGiFAqF5JXRE/MrDGTyyt8wG0+yFgPRu02bNglxIwKyYMECXXUm4kXEYPny5UIIeD3zkEMOUZ0GQrE1NTV6Hnn0K4Gb8heNRvUbpF27dilJm2tmXu2nR9XY2Kh1JFrE1xkzZgjJJBxvJmub3il58xstIJm9pIjumIgUk5XXrl0r2WOYtb+/Hz//+c/zvsueVr/+9a8lH0xc37p1q2BneuhFRUW+hUdMMnvLufv+bN68WfufYci6ujp5g+Tv/vvv1/qzcjO/98wzzygcQRTFrC3FZyWTybz+doB/ckrq7+8XQmH2IKKccu+vW7dOn+OYOjo65CWzjg2TfceMGSPUhGhZKBSSB23WWytU9dwP9MBspst15P4YNWqUxkLE64477lDolKj7Jz/5Sele8n3KKacAcOTaDEEDzgUGJj8ffvjhABx9xt8yx+YHEkseI5GIZIr6s6SkRGPgfO7YscOTzNvQ0KALBhwnw1qJREJoM8/MeDwu1Ii6a9u2bZ4q7n6SuRdZ7qGvr09/o65ZuXKlZNesa0SUjmc8EZ3y8nKtOe2K6urqvPphgLO+tDf2hyziY8mSJUuWLFk6aGjYiA+t1JqaGll5TJhcv369LHnmfZjt6ZnYNTAwIISBHgef+8wzz8gCpof29NNPy1uht5ZOp2VZ06L04wotqbe3V9Y5LWwgl8NAr2zbtm26ak8Po7KyUsgAi3LxGdlsVjwzryAWiynniQXa4vG4J8bulwdmxrXpDXM95s6dq2RAjmXcuHH45S9/CSBneU+dOlXxdFrvpAcffBD33XcfAOD//b//B8DxYDh3pOLiYg8/fnkpZtKhOxmvqqpKqA69x507d8qjYkzaTDAnCsDk9hUrViiPiTK5bt06eddEStLptK8JlW7eAMfbZNVdMy+NKB09qNbWVv2Na/e1r31N1WKZ28VcmPb2dpx66qkAcmUWbrrpJnlm5GfmzJnyMs3eT8NdS7Nys7v/065duzx65cwzz5THTOR569ateg73KfdfdXW1dAjnoLq6WnuBaN+WLVs8/e2Gy5v7+6lUSnJEr3nVqlUqLcGCjG+88YbyIoj8nHjiiZJP5qcRjQsGg1obfiYWiwmFNJE6dxK+X8Q1Ky4u9iTGp1Ip6Rny39zcrDVg0b54PK5ej9T3RPpOOeUUIV2UhalTpwqd434eGBhQvp27Uv9wiYhPdXV1nowCju7j73GftrS0KPmaqMcRRxwh2SRix3OvsbERH/vYxwDkLgT98Y9/lB4jCjIwMCCd5meuj6lz3D3QUqmU0B1ST0+P+KItUF9frznhhSDmCU6bNk3rz8jASSedpLkkotnd3S29QwRwMLloFvGxZMmSJUuWLB00NGzEhx5CZWWlx5PeunWrijLxc+PHj8enP/1pALmbId3d3coroKVMD6Cjo0Od24lGlJeXC1WgVVhTUzMiHor5TMZozTg781hY0G/GjBn6DvMnFi5cqJ409Lx4pXjHjh26jspbYFu2bJEXTY+ttLTU0x9oYGDA15i72WGcnsWcOXOUb8W8gpaWFnnGpCOOOEJ5FLyV8IUvfEHjZEE4dydf87eqqqoUyyZ60dfXN+wO7eZrJpMR0sRxHnnkkVoreiBr1qwRKkfvf+XKlUIff/aznwHIlctfu3ZtXv8kwPHs+DyiLCb5Jafuoo/hcFjzbN7S4drSQ4tGo1pHIpKVlZX4xje+ASCHWPKq/9y5c9Wjjc/9+c9/rvXj37q7u4X0kPzIgSF/HR0duunJnLHGxkbNJ9d3+fLlmnfzRiLz54iGEZX+xje+Ibm8/PLLATg3gIiu8L2mpqa8PBU/iXssk8nk5aUBTg4F9wf5Ovzwwz03Yurq6iS7zLtgj6vHH39ca0NdVFxcLN1CJKunp8dzW89vfVNWViYUhmjBnj17lFtGhEyk6QAAIABJREFUZGbJkiXKBeE6rlu3TggCb3Ax7+zVV1/VXLB1RzgcFm88n1KpVF4rG/LoB8psXq0m6svxNjc3a2+xZUxlZaX0B3Xf66+/rvONSA6fW1JSIrlgFKGpqUmybxZlJXE9/Si0WagUB58/fvx48cWIwIwZM4TaEYVrbW1VFIdryLmKx+NC0ykHoVBI/HEftLS0SIbMa/vvti+HbPi4Gc9kMvo3FUVbW5sSAsnYa6+9po1EyPXee+8VnMt7+nwNh8O49dZbAeTu+r/44ouCqc1wgbuC7XDI/YxYLKaFIzybSqXy+hMBTjVKTjqh587OTsGwDBtRSDZt2qRkYCZFA7nQCAU4Ho97DB+/Eiq5EcaOHZsnlADwwAMPaMxUsF1dXTpwCC9WVFQIXubnqYjC4bA+x9DK/fffL97IQ09PjwTbr0qq7pBIf3+/DjyzMSI3GeX64x//eF5zRo6PhgIPeyrTeDwu457Gzp49eyTr3Afd3d2an+HUfilEZqiLMkpZmTFjhuSRV0j7+vr0PsN6l19+uUKurPfCtZgzZ44MfYYIJk+enHfBAHDCve4E7uHUKuL8cy43b96s5zL0c+SRR4oXru/y5ct1cNC4qaqqkjJmaIFOiQnP8zePPvpozSv1VSgU0uFpKlg/9I55dZwK39Qdt9xyC4CcEXbWWWdJ4dNADQaD2sfkka+rV6/Wb5DvYDCoQ5TzZI6FfJnJ+sMh6rFsNqs9wwOvp6dHc0seVqxYob1qGvk8NB999FEAuXInjz32mJKHKQubNm2So0N9m0gkPMnNw2mm6x4f4MgM9QH3fXFxsRxavu7evVv7iPutqalJIWg2KTV7yXE/m6Faswo+4Ow791ntR4qEWS2Zz+VeKCoq8ujON998U+vKyzLbtm3TuW/yDDjX4KlDaAhXV1fLoKeh3NzcrLOXcz8YZ8SGuixZsmTJkiVLBw0NG/GhZdne3i6rjRbYkiVL5I2wauOTTz6pcAE9lJkzZ6orO5/Hgoetra2ybGntJhIJT/+T4uLivOTH4ZLbU62srPTAsuaVZ17lnj9/vtADhkhisZjGSQiWobyamholjBIVaGtr0xyaXoAb0fLrqj75qq2tlZVNT6OpqclToOqQQw5RAqJZzdrsmwRAvXEeeughIT30wNva2vRbZoI6n8e19AvxoUz09vbKC6QHn06n5QXSy5w2bZpQLXrLZ5xxhrwPlmJ45plnADjdgikLhKwbGxuFapHXRCKh+fT7eqkJ11NuiGJ0dXVp7EStenp6tKeIEJ199tlC7u6//34AwBe/+EV9/itf+Yo+BzjVn+k1U2ba2trkEdLLGw6vlAXOa0tLi/YTE5obGxs9RSUXLFigPcWyEG+99ZbWmCH022+/HYCDPBNpZiHLWCym5/IZwWDQ0xdwuOirW97Lyso815UjkYhQIP7tzDPPVPInx1ReXu4p+koeX331VYXZicK3trYKuTb7aLmvCQ+3wnihvei+HNLe3i5Z5N9Wr14t3cPw3CmnnCIZYOkBhpLmzp2LqVOnijfAkU2G7DnH6XRauooyYZZ9GA6ZBTzJB8+0TCaj85CpIGPGjBHKz5SKbdu2Ce3jnmWSc2dnp/Y2+e/q6vJEUwKBgM5lzqE7DD0U4hxGIhFPYnxlZaWn6nJJSYn4Nz/PKAqjHTyLGhsbpVfMfUAezAtMlBd3/7x9kUV8LFmyZMmSJUsHDQ3ZhKenQ8uyo6ND3iP/NnPmzLzO34CTJ8BELSZgLly4UJYcLVpa7NOnT1dsll6OWbSIuRZFRUWyZM2riUP1wvg9syWBu13Bli1b5DXxaugbb7yBH//4xwByxcO+973viVe3hzF69GglgtFL37Bhg7wXd/8xwB+LHcjFaRnfHzVqlDwkxtQ7OztVbJHe5ssvvywv89JLL9V7vGrKcgbf/e53ATjrxbwRegBEeYDc1cR4PK55MRO4/UBGzKRNIh/0PCZNmqS5YBLl3XffLe+fa1tcXCxUw+1tTp06VXkvTFw0C/lRXvv6+jyes1+5WuQxHA7rdznPZpIlC72tXr1aiBXH/pvf/EbeKBOZL7roIgDA97//fckHr6ROmTJFe4C5DF1dXfJQzZwHvzpfmwUouV6vvfaank9Ew+wpx4sUqVRKiezc28w/a25ult7hZ1paWiTP9NwbGxt978TO55k5PuTTLORGlIq6sKGhQfrxsssuA+C0ALrtttsA5FBnIgd9fX3qn8Rcr87OTiGt3BtmIT+zX+Bw1pBngdmzi/qQ8jpx4kTtO/6ts7NTuR/UVa+++qqndyJRunA4LCSQr9XV1fou930qlfLwM1we3ahWe3u7UF/ytXfvXu0x6oXa2lqdZdxHDQ0NQjP4DLbbaGpqUuSEOrOpqUm8ET0qLi7W/HBMfhRppEyUl5drbDwXw+GwojTU90cffXQeisox8lyknjLzu/hc8hcIBPIuOJGGgkQO2/AhpdNpQVOErV555RUtHIU4EomoP5B5Y4oNSAknU4lPnjxZNxM42WboiMqou7t7RJp4mvUKzIasgKNECKXz9bXXXhNszIZrJ5xwgvr9cJG44Zubm/U38tnV1aVQkinINHjMSqp+8MbndnV1aSyEW0eNGoWvf/3rAHLhkF//+tee2yWTJ0+WgqYwU1l99KMf1eepWGOxmJ5HYQe8kL/f9VHS6bSnLlF/f7964HBjLV26VAbZySefDMBZW/LL+jBUpo888ogOS25Ksy4RN3YoFBKPZtNNP8hM5OahQAW0bt06wcpUsCeddJIOIyaDRqNR1e3h+nA9s9ksPvOZz+S9t2LFCoVvud719fW+rR+QXxOF/LlDadu3b5dhx5Bfd3e3DgAeMMFgULLNcDMTQisrK2VEkJfVq1drD/L3S0tLPWs4XHInoIbDYT2b4apkMumphL9ixQrdiKXjUV1drfAsjVzK+tSpUxXqZS2mqVOn6nfNpqt+19Qyk18BR9Yop5z3UCiksdIwnT9/voxT3j688cYbFTrhpRfq1GXLlum5dLLNZpY8jM059otHd12ncDgsfWOGwBn653pOnTo1r1I154J6k2cK97N5LtL4TyaTCgXS8ejt7fWci36E8sxba5QZ6j9T79FZXr9+vdaJzsjcuXPFF5/HvfnGG28o+Z66tr293ZOCYiaj7w9fNtRlyZIlS5YsWTpoaNh1fGhtVVVVCYUhtLZu3TpBsoSfzZAA6eWXX5Yly6vwtOa3b98uK5/IRCwWk6dHb8wcix/1UdyJ0gMDA7JK6T1Onz5df2OYr6KiQh1pab2uWrVKHhjHyDpEGzZsEEJG77Smpkaf45wWFRWNWM0QQpQbN24UGkD+W1padOWQ8798+XJ5T6waumXLFiXb8ZopX9944w15M+Rr2rRpmjsTwXLD4cMltwcWiUSUQMffSqfTCjey7kdTU5NCVvRaNmzYIKSD6AnXcceOHXqPnnQ2m5Wsm6UI/O6W7EYf0um0ZImI1O7du4Vi0BuMRCLyFplkOWPGjLzkUyCHBo0ePVrP5X597rnnhIzxvbKyMl8TuM21A5wwD9EX8rJgwQI89dRTAKC6WMXFxeKfKPMbb7yhircXXnihxgs4yB9DvEQdIpGIZINInomG+BFWB7xyWlRUJK+WIY0XX3xRa80xt7a2KvmcMvnEE0+ID4apeeEinU4raZ9y3dnZKSS2EA9+IZLukERxcbHkhPwXFxcrMZt64cgjj1SIh+hceXm59CvXitXui4qKpIMpu5s3b5YO5jjMqsZ+19Qy0wio+3iOmcnxjHDs2bNH6A6Rk+7ubp01lG2u3e7du3U5iDrGPI8YMTF584NHdygvEAh4LhP19/drrzKh/JRTTtHVfZ7ZX/7ylyWn1113HYBcTaK6ujrtN6LlO3fulO7mWWTWoNof5MciPpYsWbJkyZKlg4aGjfiQgsGgPA4mEgaDQVnUtLZ/9atfydr9x3/8RwBODggtc3qPjAOuX79eFi096VgsllelFnCsTD8rNptFuwDHmmTcmBZuTU2NLFp6TOFwWHkitPCffPJJxbBZcI1eillEi7HM2tpaear0ojOZjO8JleSRyEdHR4fm2kR8rr/+egC5eHlNTY08EXr+u3bt0voT8WOSXlNTkyx0IoBFRUUeZMEstuX3VW+z0i6TyM3EYxbJ5Fhef/11rRELbq1Zs0ZzwHEyzr5nzx4hZ1zP7u5ujxyZvPnNI8cUDoclK0QrzjjjDHlaTHQNBAKKsfO1pqZGyfksDGf2uyJvZgFRvk8qKyvLi8EPl9zzlc1m9Xyz3xrRH+qOD3zgA0rQZof53//+90LmKPeUzU2bNmn9ua/HjRuXV00ZcLx5NzLpdy5aJpORfHK8p59+unQK3zv33HOFfHC9li1bJvSVlyTMnm1u5KWoqEietHnpwO8eXWZSM+DwzBwXrmM2m5UeIYJzxx13CPViJODQQw9VDhDXm3mWc+fOFXLNfJ6mpiatrZk3OVIVuDk2s/cZ5ayjo0O6glXEH3jgAV0YuOSSSwA4eoSXD0g8W5qamrRn+VvV1dU6L0zkxywY6TeRDyB3FrS0tIhX2gIDAwNCx5m7s2nTJskzx3bOOecAcC5G8VIBc0fNfWdGCYaS4zNsw8dU7GTWTHbiIcMNdd999wneYuPK1157TUJOJs1QFiEv8+CnoPp1w8lN7iqQwWBQ/zZvYHCDUVGuW7dOByV5X7BgAc444wwAOSFlA0geTEAu0S0ajcrwcd+sGAkeuYamMUJFYyatm9ViqZxYSfauu+7CXXfdBSAXruSm7+vr85RQNw1VvyvDFuLRDB0yUZKv2WxWypAHxFFHHaUxEzYeN26coGauIxVNLBaT4uXaBYPBgm1G/ObRzavJD+Vz9uzZchwYurz//vu1trwtNHXqVMkAeaWhVF1dLUVn3r4zq8Sar36TeRBTT1Amd+7cqZsyPOymTp0qZUudk0ql9B0mw/LQnzp1quB46p++vj7xx8+bFa/9JlN5cw2ZtG2OgSESswYP9e6nPvUpOVj8LnlOJBL6N2W3u7vbU2nbrwa6JpE3rqNZt4vU0NCgiu80BN58800ZcOZtRTod5i0tIOeMADlZ7OzsHLGK6YWI8hEOh/NuIwOOIcubotQVW7dulU5h+sCjjz6qsTLsTiN41qxZOlN5Bg4MDEgGRorcZ0YwGNTvc6zRaFSOPvdWOBxW9Wnz5iTXjs+jjmpvb9d6Uv+m02n9FvXPUPm1oS5LlixZsmTJ0kFDvrlm/f39stAYLgkEAoK/CGmNGjVKyVu8NpvNZgXX0guhpR6Px/U3EyKlFehnf65CVMg7p8fS1dWlMdGar6+v9yRbZTIZwbEcN8NBVVVVeRVXgXxIz/z9kUIKSCbiYtYsYRIkEwt7eno8EOVRRx0l9IreDNEBE+UwPctCIZ+R4tGUDzdyZzaEpHcWj8c1FqIi6XQ6L6QJ5KDn6upq/c1cfzePI7mG5LG/v19yZibp0xPmnmxraxOywde2tjaheURVzARtN4IViUQ8IdPh9jt6JzITid3VnM2eS0zonTJlSt7lAMCpJ0JvlKEx8rJr1y4PumMik2YS+YHci2a1WqYC8G8tLS15tXcAR4bdPQE5T9lsVutqIq183kggPW4y5ZSoBXVFZ2enQuT07rdu3ar1YGgoGo3K6yfSyv28e/du7UWiKGYCrvtSxUiQuSfc6GBra6ve59jHjh0ruSRKFw6HJbfklWM2E6Q5d4Vq2WWz2RE5G0355ziILldWVmq8RHC6urryymIAzqUfyiU/TzugtLRUf6NuMtdruMiWRXwsWbJkyZIlSwcN+Yb4mCgMvfrdu3d7PIgpU6bIquPnMpmMUB0SrULz76aHzt86EJ40yZ2TAuRXqwTyKzybRRaZO+KuZF1bW6u/mV1uC3kjI4VqmeT2Tkyvg/y0tbV5uu+OGTNGV4yZ+EweI5GIJ1HSvNY9UvkS70SFEo4pT5z3np4evU++S0pKxAd5pJcWiUQKyqDZywk4cHJq9iMCHDl1V3CdOHGicgzMXDnyyJwzPiuZTHpKRpidnv3qW/VuZOYVmZV/mTvA3K1YLCZ0g8hCcXGxxkYPlLyYcmrmFbj3/YFYw0JUWloqRJJzbepHjjMWi3mQW+YbplKpvKKv/J47AfZA8ejOYezr6xN6x/XZu3evdBARBDPn0o1amsikucfdBUMPFI8mwgU4PLoRtkwmk9c7EHByYdwRBSJEqVTKk1tj6tFCZ9VIUCAQ8CSIB4NBnYHmJQDyUKhkQ6GzwOyawO8VSmQeyjr6ZviYA+GGSqVSnttXPByB3CKaG89dut38m1mZ9r04LN0bxlSK5BnwQnN9fX0FIUjAUbZmSW7SSN1uGixxTCbfVESJRCLvsACccdIYMA1UkntdC83ngaJCzV7dhoIJpZqHgTuMyddoNDoiFVKHQqYxYsod14CHIADP5zKZjBSOW3kWSsw25+5A7UkTvqf8mbdnqCh37tzpSdY1b2fyoCnEnym779U6un/XrB5f6HPmTR4aem59E4vFtK6FLoYc6L3onm9z3rm2dXV1nn0HwKOD+P/i4mLJohnieq90aSH5MeUVyK+Hw/dqa2vzanMB+SFLdxVj87cOpMy6ZSyTyeTdDnSPzXQu3Gc7ZbK/v98j1+ZvDZdsqMuSJUuWLFmydNBQYH8sw0Ag0ArgrZEbzojRxGw2O+rdPvQ+5g/4v8/joPgDLI9/42Tl9H/J8vg3TZbH/6X/i/ztl+FjyZIlS5YsWbL0fiYb6rJkyZIlS5YsHTRkDR9LlixZsmTJ0kFD1vCxZMmSJUuWLB00ZA0fS5YsWbJkydJBQ9bwsWTJkiVLliwdNGQNH0uWLFmyZMnSQUPW8LFkyZIlS5YsHTS0Xy0rotFolh1Y30+0Z88edHd3v2ut62g0mmXvpfcbNTc3tw2mGNX7lcdEIjGoNQSAWCyWZU+f9xN1dHSgq6tr0Dy+X9dxMDyWlpZm4/H4gRiSr9TZ2YlUKjWoNSwrK8uyH9r7idrb25FMJgfF48GwjgfDXiwvLz8QQ/KV9u7d+45ruF+GT0VFBS677LJhD6hQT59CTSxJhfrnuJ/h/r5Jv/vd7wY1rsrKSlxxxRWD+uz+kNlXxd2Uzxy32fNkf3uSfPOb3xxUZc3h8FioQZxJ7gaH+2oot7+FM3/1q18N+rNVVVX4/Oc/v1/PLzTmQvy4e+EUWqd9NdDbF98/+9nPBj3eyspKfOYznxn0583fNsfubqJq/tu9xwbbGHBfPP7iF78Y1Fjj8TjOOeecQX3W/buF1qbQ3irUfHQw+25fn7nrrrsGPd6amhp89atfHfTngcJzW2id9qVvCu1B93P3xeM111wz6PH6tY77Go9b9xda9/2l/VnHoexFkjk+nm9mM1V3z8Z96af9pcHuxfLyclx44YVD+o1CZI77nXSFHz25brnllnd8z7cmpftDXExTYNmcjH9jo8SKigp1IGZT00wmU7DD9ntJpnFGJWM2YGPjOfJFC7qnpyevmSngeFRuvt6rBnuAV7GaBybXK51Oa/xcL7MRn/uQ6evr82zcUCj0njWEdPPT39/vOTRKSkrEW09PD4Bcl/a+vj51JDb5ea+bzZrknttsNqsu0YUajbLxLhsklpeXq5s756Szs1M8HujGwW5yjyObzRbsHM2xm53rAWcOKLN8VqEGkO8luRs9BoNB/Y1NLtPptOSSTU3Zsb6mpgbt7e0AkNfIlI0++fn3Ul4LySmJa1dcXKw9yPcpr6FQSI2iSWaD4eF29vaTTH1oNugE8vUs9x11TFFRkd4j32ZDVs7Te8Wfu4FqOp32yCmQk2OuTSqVAuDwSdSeezKZTBY0DodCNsfHkiVLlixZsnTQ0IggPqZXYnrQgOMh09Pie7t370YikQCQs1SnTJkCwLHoOjo6AOQ8tNLSUo93FwwG9xnu8pMv0zvmeGnZhsNhjYnWaygUktVKz4qWa3FxscZNzzOZTHo8cBM9ORBWvBnu4BhMuJz/5rrt2bNH4+d7zF8YGBgQv5SDSCQCd+z/QHnU7t8xx0cvsru7Wx5YXV2dXumt8JVrV1lZKfnkqymTw/VQ9pfc4QLAi45ms1n9zfT4TVkDcmM/7LDD9N7bb78NAGhubtYziBaEw+ER9zj3Fabib5sIFPkLhUJ5yCoA6ZdsNqt9TGQ2HA7ru3zPRIEO5F4018sMfVDeKJOdnZ3o6uoCAEyePBkAMHPmTADOvK1duxYA0NLSAsCR3VGjnPRAU58ON5QyGCoUpnKHXwcGBjz6MxgMSr/u2LEDQE6+J0yYoOdRFkxk3URhD8T6uUOLZgiL+iaRSCiiwbWLx+NCeKZPnw4gdy5Go1G0tbUBAN58800Ajs7ic7kXDyRKafJpRjsAZ22ITJHPRCLhifDw89FoVCgX56irq0uybsrDUJBmi/hYsmTJkiVLlg4a8g3xMa0uevVAzgthPDkYDCpPgt8pKipSzgutPH6mqalJHhYz56PRqH7D9K75PP7NTzK9A9M7ZiyZFnZ3dzd27doFIJez09nZidbWVgA5b+Poo48GAJSVlenzq1ev1vMbGxsB5MdqD4T1zt8w85TcvxsKhWS1c+xvvvmmPK7q6moAwLRp0wA4nuXKlSsB5LzrRYsWac74W0Bu7UaKVzPWb8oJ/71z504AjrxS7ug119bWig96mfRGgJzsUiZ6enrEB9GtoqKiEV/HbDbrmcdMJuPJcYhGo/IoyWM2m8WDDz4IAHj00UcB5LzNj3zkI/ruPffcAwB47rnnUFtbCwAYO3YsAKCxsTFvTUeC3F50f3+/9j/XpLe3V/NOWaysrMTzzz8PIIcQ0BPt6OgQSsm1DwaD0mH8nJnrNVJ8mjLCsYRCIe0Z6r/i4mKtNflZsWKF9uXUqVMB5FCQ5557Tvxv2rQJALB48WLMmDEDQE6PpdNpz3NHggpdIOAYOO9lZWXKUSIy1dfXJ51qjhkAxo0bh3HjxgEA3nrLufOxcuVKnR98DYfDnryakeIPyEeaKEvMxWpubtYZSeS8trZW8/LUU08ByOmnI444Ak1NTQCAl156Sc+fP38+gPycRXculN/kzucJBAKe/dHU1KS1oM758Ic/jAULFgDI6dPm5mYAjj6iHv3LX/4CwFlLrjV17ahRo/L26mBp2IaPCeG7IeZUKqV/UwFNmDAB9fX1AHKL3tTUJMEmlEdD6He/+x1eeeUVAMAHP/hBAI6Ac7IJV2ezWY8R4geZ8DkNHhMG52bjoq5Zs0ZKh8qkpqZGC0p4ls+aN28e1q1bJ74AR+C5Ic3yAYT3+J7fCmlgYMCT8JnJZDxjicViEjwq1MbGRh0uFGyO7/jjj9f6PvPMMwCcw5Qbkps5k8lobs3QoR9EOTSTCPlqhnZo0G3btg3HHHMMAOi1p6cHL774Yh7fPFgCgQDGjx+fx8+rr76Kbdu2AcgZujQKAf+NPDM0YB7+gKPYud84x+l0WgmElMdoNIqPfOQjAHKyytfrrrtOe3f37t36XYZMGBI0DSqOw0xm94NP8mUenPwbD4RkMoklS5YAyMnRL3/5S2zZsgUAcNZZZwEATjvtNACOEc/Dh/OxefNmbNy4EUDOGauqqvLIp19hdpMfzqGZjG0mYgOOHHKs5N8MsVLGuUbBYFC3Ojn22tpa/ZYZPuLhzFe/yUyFMM8Oygz1aGlpqfYv99aTTz6JMWPGAABmz54NAHj44YfFF/cbDZqBgQHxS0M+FAopZMt5NR0ZP8g8F7nvYrGYZIn8p1Ip6VeecxMmTJBRc+eddwIAli9fDsDRj5s3bwYAbNiwAYAzD3Q+eBa2t7dLphlC8/PcMEOT5Km6uloyyXBcT0+PxsSzYPHixQq78oYZ/3/uuefKoeK4Z86c6Tn3i4qKpL8LJa+/E9lQlyVLlixZsmTpoCHfQl2hUMhTa6Czs1PWFyHkxsZG/ZvW3U033aTkO6Ik9KhPPPFETJw4EQDQ0NDgDLqoSJY6Pc++vj5Zz/RizfDXUMm0Humh0ytqamqSJ0WvKJVK4YgjjgAAfOELXwDgWPisQ8Pvkpf+/n5Z+vSm582bJ0+NVn00GtXvm4nPfnjRZriA1jUt6q6uLg/MXF5ejpdffhlAzsofO3Ysbr31VgA5VIc8Tps2DcceeywA4OKLLwbgJMo+9thjAIA33ngDgDM3hKiJjJSXl/sSTjBDePQM+NyGhgZ5I5ShiooKHHrooQAg1OZHP/oR5s2bBwCe2iQ33nij5mfx4sUAHK+ZaAE9yVGjRsnzZGJ4Mpn0ZR3N2i1EJChvPT09QulmzZoFwEEICKHfeOONAIBPfepTmDNnDgAo3HrKKacAcEIolPfPfvazAJx99/rrrwPIeVwNDQ36tzvs6wdlMhnPXojH49IFDGWMGjVKeoRz/frrr4ufD33oQwAc9ABwZJ2oCRGQOXPmaH9STs2ws9+oq4l8kDcTyeJ6El3r7u4Wv/xbRUUFXnjhBQA5/cG52bhxIxYtWgQAOO+88/SZZ599FkBu7oqKioSWmGE1P+TU1MlutCAQCAjV4b477LDDFDFgOkBjYyP+67/+C0AucZvyescdd0j+uZ+j0aj2J8+HdDqtdSYqMpQaavuibDarMZiIIeeZKOybb74p5ObVV1/V3yhzhxxyCICczDY2NuKoo44CABx33HEAnPniHjeREeryd0okHgqZ4S3KB+fcjAhQ7mbNmiU9QcT1n/7pn3DllVcCAD796U8DyJ2Bp556Km677TbNA+AgdVy77du3A3Dmj2gd90Z/f/+77kuL+FiyZMmSJUuWDhoaEuJjxpBp+fX09HjQlXA4LOud+Q8vvPAC1q9fDyCXO7F27Vp8+ctfBgAhCbR0Fy5cqFguLbuKigp5N3wWAE8y3nCuuLv5S6VS8hr5umXLFlmgtL7b2tpk7X7/+98HADzyyCOysultcowbN24UysJntbe3y6JljHTUqFHyeshnJBIZstWHxKdOAAAgAElEQVRuVv40r3K7r1QWFRVh0qRJAKCY665du2TJn3HGGQCc3CyOlZVdaeFv27ZNcXVWJ168eLFQO37PjPmb6MVwEB83umOiBVyTKVOmKK5+//33AwC+973vyZOkh3LOOefIuyGSQXTr97//vbzRm266CYDjZTLZkMnDdXV1nsT87u7uYSXkuz3U0tLSvHIJ5JHxfyKuzz33HF577TUAORSos7MTX/nKVwDkPEmu0+rVq7XfiAotWLBA+WtmPgm9PyKhZmHP/aVCMs7n04uur6/X3+ghTpgwQXuVeXQXXXQRLr/8cgCQR8n8guOPP15eo3nd+KSTTsr72/bt2z3XkSORyLCQAvf1/Gw2q7FwLyYSCekIIhR33XWX5p2owAknnCDknAgl33vooYeUoP/0008DcNZ1xYoVABx9C+TyZswxAf5cHDF1MnNB+BqLxYSIkv/GxkbpD+bYvfLKKzj99NMB5BJdeU60tLTovOEevv3226Wzli5dCsBBt7gXebZQJwyFzIsTJDMflbLY3t6ueeR5V6gswTHHHINrr70WQC6BmWv3i1/8QjqFr0uXLpXsM9/y1Vdf1e8TZSouLkY4HB6SvO6rFIiZr0SkkXty+vTp+n3uu49+9KNCJn/zm98AAC655BIAjg4lEnv88ccDcHSTqc8AR264B83SIe+G+AzJ8DEF11SwHBQVXEdHh2BibtTm5maFggi1Llu2TBuNSsY0oh5//HEAuczvQCAgoacCNmvfmFneQzV8+PvcGF1dXYIMOY7x48erlDchuocfflghHIY8zjvvPIXraLwQ4mxvb1cyKQ/T9vZ2z62hqqqqgtUwh3KYvFN9DvNGBfmpqamRkcmDvaWlRetKpXPGGWdIGBnWeuKJJwA4Cd+EMletWgXA2dRUVOR/586d+pu7Qu1QyKzcy3ns7Oz0hETi8bgSYnkYJBIJhfioiIqKiiTvzz33HICcDB933HEqc2/WR+HBTwcglUpJBnig9fX1DSsk617PbDbruVVRVFTkkZ8ZM2bIOD/11FMBODe5yBuNHK7xkUceKePppz/9KQDHGObfaMAGAgEZyQwh8v9DoX3JqXnTk7/Fz69bt05jp4KdN2+eDJ0//vGPAKC2EVdffTUeeughALn9ee+99+r2E58bi8XkIJi1qIZ6kJjhFdNA57O5BxYsWOC5CZlMJmWsMDR04403ymjg5y+44AIAjtH24Q9/GEBO/ioqKhTy4XzW19dLB/EZfX19wzLu3Hu6v78/r84O4Mwtb2vRoIvH45LFE088EQBw6aWXyhggMdS1fPlyhY14eJqGNw/lSCQig9Bdd2ao/HEfm/WW3PXN2tratD+PPPJIAMCFF14ofn/yk58AACZOnIjf/va3ABzHCgDOPPNMAMDpp58u55hG4Y4dOyS35uUC974fqgNS6Nzv7Oz01Gjr7e1VGgu/c+KJJ2q9eBFo3rx5MmR5PnA9tm3bJvlk+6EbbrhB+458jho1SrLO+RuMjNpQlyVLlixZsmTpoKFhJzfTGygtLZVXx7+ZYQVaoKY1ePXVVwNw4H9abbSYafklEgl5bbToN2zYIKuOf+vs7JQVyN/s6ekZdqjLTDbk2Ji0O3/+fHllhE/vu+8+fOlLXwKQCwPdfvvt8vjpeTJ8cumllwoVoKdTVVWVl/wMOPPrTh4fGBgYkofiroFiXs1lAiCRl3A4LE+SSXdTp06VhX7HHXcAcLxG1mQgzEwv7oILLsDJJ58MwEme5XtE/mipb9u2LS/8AzgyNFQvMxAIaP7olSQSCa0F4fWBgQF5iPTO/v3f/12wN8fX09Oj66T0QK+66ioAjgz/6U9/ApAL8b344ovy7PhbTU1NQtDMnmZD9TTNEgTm9XjKKvfE9u3bVSKCYZDW1lYhsazLk06ntVaEmO+77z7xQITo/PPP1zzw80SKUqlUXqIjabiJsSZiQF4ZPjAr+XLd5syZI5SWYbspU6ZojSnjHOtVV10l3fSJT3xCv0nZMFEroktc16ESrwO7w87d3d36N/np7u5W+QTurdNPP106iuO8+OKLpV+ox3hZoLq6WrW0yM+4cePEB9GD0tJShdW4F4eqb9zfNXnl+hBBNuvp0Lv/zne+o/Ak0dTNmzdLX/ISAi8SnHzyybr+vWbNGgCOnuU5MnfuXAD5vZ/MNAk/kpvN6t7uvmGNjY2eM+2VV17RPBNpmzBhgtaW+43nwrnnnqsLCdzXhx9+uHQLZbykpETy40ZE95fMitOcr66uLukYpkREo1HPJZ5AIKC9xUjIc889p3lgVIdrvmDBgrwq3YCzNvw89dakSZM8IUJ7nd2SJUuWLFmyZMmgISM+7jhhKBTyWO29vb1CEIgCJJNJ5VOQurq6lIR22GGHAcjFZhOJhPJ+aAFu2LBB1h29dz4b8Hba9oO/0tJSWdZ8fm9vr/IE6FlUVlbqu4ylB4NBJW3RIjevhtNrZez58MMPV1IiPZzW1lbx7O6lNFRy9+Ay+4Yx1h8MBuW9MFF34cKFGiv/NmvWLHks3/zmNwFAhSej0ahyQoie7NixQ9/ls8wid+6eREMlEx1zE3ncuvX/t3e1wVFeVfhks7vZryRsEhICCSSEAhXwozAU8KMZFWQK4kfbKVOr1nGqHasdK3WY0amD1vqjU6HO1BmtzsjYL4sODErRKW3TYgMUiiAfgQBpKCSBhCQkJLub3U12/bE+z559d600+4Ifuc+fhJC8+957zj33nOece+5ZRsGoHfvoRz8q3/nOd0QkHS2vW7eOugu9A9PX0tJCOaKGqL+/n8XsiIBaW1s5T/lGYNYxArowFlFxX18fx4GoyufzUacQSfl8PjJCYIHAZHm9XrJ6KOZfuXIlDylAdqdPn+ZaQbSZT+sFa21INBrlHGMteDwefibmVTPJ+g4uMNKor9i0aRPfEYWiqHGbMmUKn4s1Gw6HM1gQkfyKfnWBKL7GYjHWOOAz/H4/5QW7oJtVgqGrr6+nTqD7NnTzyJEjLGTHAZI1a9awBvHs2bP8fWsDw3wZO92IUSRTZviMeDxOPcV4Tp48yfoxvY7AWIHpQQ1JVVUV9xGMdenSpZxPsLXV1dVkyYB81qJmRPAc3eUb+6PH4+E7Q/dqa2vZygOyqqur476JQxd41gsvvEDGB/ttW1sb7Q3muL6+nuO2Y9/Qty2IZDaGxFe/3082FfbnueeeoyygY06nk+w4bAhscktLC/UTz5g1a1aGbyGSqv/C+Kz1Ve+GcZ/qypV2wWRjYCJpqh0vd+HCBVm9erWIpCm6PXv20Nii2GnXrl0ikioexYSiyHDatGk8pQGqFFXseBe853idH2s6yOFw8H11kRw2ctB3y5YtY3EaNpO7774760QNNs4DBw6QIoTAqqqq2H8EBl5fsgcHMF9DZC2odTqdVGgUWp8+fZopKVDfmzdv5vz/9re/FZGUXPE9lB5poNbW1qzL5fx+Pxc/vtbW1madbsnnRJc+uQYUFRVxcWGDHBgYYDpv4cKFIpIqasWJJ6Tz6uvrKReMEamvefPm8WQYdEI77ZivlpYWrglsrvlAOxRaP/BsGE4YUxFhH5djx45lbC4iqVMjeFekcdEFd3BwkL2a4JhPnz6dmxLWaUlJScZll/lAy1CfwLFeEut2u5kiwFjfeeedjM6xIiLHjx9nN2ccjFi/fr2IpFKAcNZ1YS8CKqxnt9tN+6BTM/lsmlj7GJcuE4A+JZNJprAw193d3dRZyObUqVOUP5xcbCw1NTUMNHBab3BwkDLXBbBWpy7X9TVXC93BONcztIOKQnvIYt26dRkHSkRS6w16/JOf/ERE0ralr6+Puou5e+qpp2g34cDqvUH3hRqvHPXzdFrP6vA5nU7qFOz7+vXrWayMkgKHw8H0MX4GW9ne3s49EweDdu7cyf0FNruoqIg6mu/1R7n+zu/3U2fg2DkcDjqlcFo8Hg/nHXa1uLiYtgX2B/Py5ptvclywzffddx9TYpBrIBCgrJH+uhqYVJeBgYGBgYHBhEHexc2aokW6AOmAeDxOegueanV1NQsNd+7cKSKpNBE8Q0RmYHACgQC9XnibixcvZv8UzczoY975wnpE2OPxMGLAz65cucKoA+M8cuQIIw+ktwKBgDz77LMikmZNENnNnj2bbBjYAd0nR9+/Y+2XkG+XUc2MWccNGXZ1dXFekY584IEHmMZDJPbCCy+QEfvpT38qIunO3I888og8+uijIpKeu7a2NrJ6+LtgMMh3yaefBqDvkYFMXC4XoxF9lBbMAPT05MmTGbSrSOZFhwAildLSUtL1YBxqa2t5JB7PTSaTWV2M85WjlX72er0sKgSr9fbbb2dFXF1dXUwJ4GdHjx7lkWEUXuLfb731lvz617/O+KympibOJyK+kpKSrHvI7CgY1Rfn4nlaT7BWwFaWlpYygsT4ampqmC7QhZQiKR0G84D3njlzJn8P/Yqgr3aNL9dxdq/Xy++R+vF6vYzokZK74YYbMmSHZ+BdEe2D8dm/fz9lB908e/Ys2QbodyKR4GdZx5rPOEUyO89bL+sMhUI87oy11dDQQAYLF1bec889PCiC9XTXXXeJSGaaBC02fv/73/PADBi/4eHhnDbQDsBWDw8PU37Qu7a2Ns49jqfPnj2bdgPr9MCBA9xTwbDecccdIpKSI1gd7B8iad3Ez3w+H/fUfNeglj/my+VykXHBQYbLly9zr4Rt0BdVI0szdepUsnrQO6znn//85/LEE0+ISHrdNTQ0sGWILmvBngq9uRoYxsfAwMDAwMBgwmDcjI81oovH4/S4wAKUl5czL45CybKyMjYJ27p1q4ikvLy7775bRNKeLYq5tmzZwmgc9QilpaVZnWl13RFgx43J+lg7omd4uF6vl7U78NZfeuklevEY+/33309v/7vf/a6IpHO7p06dYgM/eMkPP/wwmwAi6vP5fFlF23bcYSWSWU9jvf324sWLWd2cH3roIRYBo1Dw4MGDbAQH9u6xxx4TkdT9Mqj7gnfucrkyGm+JZDb3swMFBQWMbjFGj8fDn0Ge/f39jBBRb7Vs2TLmjL/1rW+JSCoqw7FavDtuhO7r6yMjhi6kixcvZidVfQs0xoj3yPe+J2uDMr/fT/ZFF8siV47j6cPDwzzai2g4Go2yjgRMK9jX/v5+sj+oL1i/fj3rnlDjVFxcnKWr442oc9VceDyejO7lIin5gqGA7i5cuJBzArkODw/LM888IyJpRhIM9JkzZ8iA6boe1MRAHxwOB2WoawDHC32AQD9HM2giqQgZ7AbW2OzZs2Xv3r0ikraPt99+O9lUMLeoY1q0aBEZMejwlStXqCf6ridr0Wg+0IW/uRhmzO3hw4e5L+D9SkpKqIsY98svv0x2ADoJ5u7RRx+V2267TUTSRfhLlixhfRA+PxKJ0IbaxfxY6+2SySRZN7C+M2bMkI9//OMiIvKb3/xGRFKHeaDLYD/e97738Wd4d6zNHTt2sHElGsvOnz+fa1XfNm894JHPcXbr9w6HI6NVh0jmoQ4c5gmFQpQxWkXs2LEjK5sA2zR37lzuC/idlpYWsnxgxSKRCJkm7LFguN4N4+7cbDVsuv8BhF5fX8/NBVTl2NgYnQQU6AUCAToCaGeNQuaVK1eShgVde+7cOdLaoPSDwSAnVnc/HS+sBq2oqIiGFZ8zadIkfg9Hrb29nYYXn79o0SJunkiJwQGKxWJUDlx1oNNqeH4gEKBRsouWzUXT6+JjkVQhuT6lhJ9hI3nxxRdFJLWYITNQ71jAd911F2X+u9/9TkRSRes41QX60ul0UifsGp+1SN3n81FnkS6YPHkyi+qxsXz+85+nEw6qtbGxkU7qX//6VxFJp8FuvfVWzh2MU3FxMfUfOjw0NJRlgO266FIXFEN+oJdPnDhBahwXrB4+fJipHRjMefPmUaZPPfWUiKQ7HJ84cYKbEdbCqlWrqBf6MkvMox1pZyv8fj8dDxi5eDzO9YENsauri8WTSBkUFBQwWEFwAds0d+7crD4hLpeL61n3Y7EjqNKwnrAsLCykIUe6wOPx0JGGnXzrrbe47nAqSCRtFzE2/F0oFOJnQf+3bt1K5w+fefbsWaahrBdf5gsduEFnsO6dTiffAXoVDAYZcEBPt2zZknGKS0R47VFDQwM3XuwTa9eupdzhKEYiEX6+3sjHi1zz4/F4OI943ylTpnD9oMt/VVUVbSrszptvvsnN/0Mf+pCICPsTTZ8+nT214Aw8+eSTDLCQJgyHw9QLu07KimT2gIMzigDZ4XAwWMD7t7W1Me0Ife3u7qZNQtEy/m7JkiWybds2EUmfYDx//jwdOsyfLt5+LzCpLgMDAwMDA4MJg7yLmzXgyetjg4gW4JV/+MMf5v1G8Gybmpp4GRsiaHR1XrBgAdMkSHmdOHGC0TWKxPTn2nFJKQDP1uVy8fmIMl0uF48Zwou+99572UkUvYgKCgqYBkRBN4qzly5dSo8ZVOgdd9yR1S7A5/NxzIhi7IKmQhFtIfWBY9si6dRHf38/WQBEwQ899BDnHeMG9bx69Wr54he/KCLp7rIzZ85k6kUfs8TnWwu584XuO4GoDtFwIpFgHxNEI9u3b2fhHdiCQ4cOUU/xfmBPYrEYL3pEWmHfvn3UH4zV6/VyzvItFrUCctRHsMH4tLW1Ma11zz33iEhKno888oiIpCPKJUuWMMWCiAuR2h/+8AeyX2Ahli9fzvvX9CWIdhVUakBuHo+HBaNIVwWDQUZ+YLuefvpppiLxvg6Hg+sIHaehr3V1dfwMpHDdbjf/FuyVy+UaV5T5XqC7eSM11d3dTXuDlNwtt9xC5hQ6durUKeonWHIUxW7cuJFpFtik3t5eyg5MUVtbG+0M7J7uRmwHdCsGHMmfNm0aGTvI7vXXX+f/IyX9/PPPMwWIgmekvAoKCrh20YOqsbGR48HXrq4uPgN2J9+DBoDeN6A3kM+hQ4fIXGGv8Hq9cu+994pIeh84c+YMyyYgMzAdK1askCeffFJE0qna6upq2q/XX39dRFLpQqSRwGLaMUaMb3h4OCtdWVFRwTkG019ZWUm5wid48MEHmbLasGGDiKRTWGVlZWSL8Ps1NTWcL/gTDocj6y60qzmubxgfAwMDAwMDgwmDvF14XSgKzwxFTq2trWRr0LBv8+bN9MJRBzBp0iQ2u0NEiXuuvv/97zN61PdXoaAS0Z3b7c66q8MOtkDfbm29hXZ4eJiMCAoL58yZwzEjrz4yMiLNzc0iki6yRHTy6U9/mjfwIqpZsGABowPUFxQXF2d0rrUDmCfdWAvFx4h89Xg0C4RIEtFycXExv0dUBo992rRpLCjFPWZut5sF76gzWbZsGXP9+lhxPsyItcbE6/WyaBPvV1ZWxkgCDMng4KB85CMfEZG0jnV0dJAtQASGuWlqamJxL6LxeDzOaASsgdPpzOiKbQes3a7j8ThriqAzFRUVXEfIpx8+fJg1S9DzpqYm6hcYIkTUt956K2UGzJ8/n2sRYx0dHc1ZM5Evw6WPYYOtAwuZSCTITEE3Y7EYo91vfvObIpJigX784x+LSJqZQ6S6fPly1ilAh+vq6sgGgvnzeDxZt2Dna2tyHcwA0wO5lZWVsS4HdRurV6+WpqYmEUmzqcFgkHd6obM4CmGrqqq4xiHXSCRC2wpWPRwO237U2yp/3dQQNVsNDQ2sxUG9SkdHh/z5z38WkXTB8xNPPEG2BmMEGxIKheSXv/yliKR1sre3l58PFiIajdIWWG+9Hy+stVpTpkxhjQ/GePLkSe4HkFN1dTVrA8HCVlRUkDVHwbe+NQDH99E4tqOjgzKFrk6dOpVsFnTWTmjmE+tk+vTp/CzIK5lMslYH2ZzPfe5zXIPYF//4xz+KiEhzczNt6w9/+EMRSa011OzponSMFe9i7uoyMDAwMDAwMFDIm/FB3s7tdmfdEt3T00MvF8yIPh2FKLuhoYHRN2p2cGph9+7dPJKom/nhuYhye3p6crZYtysSc7lcjLzgiZaWljLXCG/26NGjjMpQS9HR0cGaHkQpiEh+9KMfMWpE3ndgYICsGaJcp9OZVVcw3tbj1rHluh8Icm1tbaX3DqZi5syZvCcG9UldXV1kCBB5w4vftm2bfPvb3xaR9F1YLS0tnDNENbqeCJGnziGPB4iQMNaioiLqGmQyZ84cnvDBvB85coS1ODiFtXv3bsoApw8gn23btvGIN05elJeXkw2BHoZCIVtProlkn0AMh8NkU6GfCxcu5P+jNsDj8bDlAE7iHTx4kO+Mo7aIGCsrK7lmwcidOHGCNUG6sSfYXx1J53vCC3NdVlaWdav2uXPnyLSBtTl27Bije4zhb3/7G5tvggVBo7Ti4mLKH2Px+/2cD5yUiUajfJ6dNUwa4XCY747P/eQnP8mTTmARNm7cKIcOHRKRtPxvu+02+cUvfiEi6TUIVkgkzXDB1rrdbn4G1l1vby/1X9vQfNgffRJIJCU72BkcyT527Bj/H6xeZWUl3xUMwujoqPzgBz8QkfSxf7DjyWSSTALet7u7m3oBe1ZaWko9RR2TXdB338F+oM4qFApx3GDaCgsLueeBkVu3bh3lgXo7rLtwOEz2FWvyjTfe4HpD3c+sWbOyTkBeuXIlb/ZVN9GFrcH6GxkZ4T6C9bls2TKOC6xNQ0MDx4XrKaDzf/rTn8iqg9HZu3cv9R6+wOXLlzMaOF4txu34WB2KQCDAl9a9WHBmH5v7vn37+KJQwA0bNrBYERQ9KOp169ZxQ4Rih0IhPgPK3NPTQ2OEzy8sLMybptXUp9Vwl5SU8N0w9qNHj5K+BB39yiuvcDHD8UFqLxQKsYcRjNrTTz+d5RyOjo5SwaxHtMcL/D0WU19fHwse8bNEIsHfgyFqb2+n7OBE1NXVyapVq0REsooI165dS6XHQn711Vfp6OGySL/fT3obY7WruBl6oC/mRCrS7/dTLvqOJhhDbADBYDDrQlkcg9+wYQNTDTjqfuedd9IJhO6cOXMmowWEnWPDnOmOtNDP1atX8+AA1uKkSZMoFzihn/jEJ2jAcFwWG39dXR2LfrHWnE5nhkEVSRllazdpO1pLYC3qLub4v+LiYqYTcbz3woULpN+xttrb2zkurDEUpS9atIhBC1osuN1uylV3F9bFsHYgV/8XGHzoTjAY5DtDDufPn6e8vvCFL4hISsd0PyqRdLDW2dlJncDX5uZmzo++9BlpXcy10+m0ZbzQzUQiQVuGAOqNN96gsw4HtaSkJKtFyCuvvMIiYIwbuvbiiy/SvkIX4vE4HSToazgcphzhMNhdtF5UVEQbjs+9cOEC5Qd7U1NTQ0cccolEInQIsQa/8pWviEjqkAwIAdjPc+fO8R5MlE3E43GWj1h77+UDncrGvCOt2NbWxuJy2M76+nr+DPdadnR0UN9gJ7F3V1dX0ydAavr9738/7TTssM/n48/eSwmBSXUZGBgYGBgYTBjYVtzsdDoZIYC+8/v9pKbgeR8+fJhH1uCZ7du3j147PFuwBy6Xi4WGYAuKi4vpvSIaGxsbo9duba44HsCjxZicTifHgihhYGCAEQIippkzZ9JTBRUZj8fJ/iCy2bhxo4ikircxH2juNzQ0RA8YEfno6GjWPUL5AvMDpqCnp4dRLQoMKyoqWGitG2CtXbtWRIQdYufNm8ciOxQIo9h3ZGSExysR6bhcLkYqkNfAwACZPLsiL6scfT5f1t05fX19LCxE2u3vf/87I24wJENDQ0xnIVKB3n72s59lUSKilpKSkiz9iEQiZJLsSnlZmbtQKMToB+vk4sWL/Fzo4owZM8hsoJv67bffTlYBaxGRsm4WBv3w+/1kkhCFBQIBjs0OXbWO7+233+Y7oeC+q6uLETV+5nA4eJce2kgEg0FG0Xhf6Nz+/fsZPWJtdHZ2Utb6BnGsBUS0+TLL+qi+SEpvrWxhTU0N3w+Fz2VlZSxyhXyfeeYZHtUHcw6b3NzczDUOuYVCITLnmEOPx0Md0sfY872TTCTNnCUSCdo+MG0zZ87kXMA+DA4OkpHEOMLhMNkPfP3GN74hIqki/AcffFBE0mmSW265hTYAMisqKiL7a5e9sRZQ9/b2kh3G/nX27FnaILAxsViMjDqaGjocDv7N448/LiLpcojt27fLfffdl/FZJ0+e5NrF85PJJFl0O5tu6uJi63F9p9MpCxYsyHi3EydOsHkvdOy1115jmxPIBMXNf/nLX9hIFfYU7W9E0gc0otHouA6LGMbHwMDAwMDAYMJg3IwPvCt4yoODg/xeFx7jGCKK6z74wQ/S84N3umbNGtbFWH9/YGCATbvQ3rqhoYFRGD4rHo/To9fFnuP1cvUxdpFUdKCbCWLMiJpQS3DTTTeRPUCh5IoVK+gVI7p8+OGHRSQVxaHIVt9yjfwt2Ibu7u6MKwlEUpFgPpGm9e4WfVcX2Jra2lqOA9FJZWUl5x+Rf1NTE/PVqFnavXu3iKSibXj0KLqbOnUqC/x0e3XMO+Yr3+JRXZwukppjRE2IPJxOJ6NL/Ky3t5ffo/DugQce4HNwjBrv3tzczLnA88PhMNvj69oJa5t8l8uVVzRmvYE+Go1y/hDJP//889Ql3LpeXV1N9gMMRiQSYYSIdwbLdfDgwazamnA4TDkietaMCJBvIT4+SyTFmiLKAyNaWlrKeiuMvbGxkRE/rgu4fPky6whRzwbGYHBwkGOAPSooKOC6RETrdrszanFEUvOXz1Fofdu1SOpwAewMoub29nbqFtDT08OrbsAw7969m7UeiKDx7osWLaLOwk7V19dnHWd3OBxZdS/6vq3xAH+L53V2dlJWaB3h8XgoU8ju9OnTZMoh48HBQdbO4GoVFBF3d3ezfg9rMhKJkC2DnMDg6XfLdTfce4FudSKSqsHCu6P2b2hoSL70pS+JSNreXLp0icwQ2MwZM2awjgmMMepduru7uX/iCPvOnTupj2B8otEobYCWo11Zg/C6SDAAAA0VSURBVOLiYuoRmLwbb7yRNhP7Y2trKwvTYS8mT57MeXruuecynhsIBOTo0aMikl6fjY2NbF0AWbrdbq4T4GoaNOZd3Kzv5MH3oGtDoRAnBfT6nDlzKAAssosXL5JqxyJGgVddXR2dAN2ZEQ4PjP3Q0FDG/+cL68bh8XhoCEAp626xMPRer5ffI21SU1ND44U5AsV7+PBhzhecp9raWlLUSOXptFq+l80BVmPr8XiYJsD81tbW0ojAAaqsrKTCYrH6fD7elQMjigW5dOlSjgfvPDg4SEOAxV9eXk5H064LWK0YHBzkpqaLgTEefP7JkyeZskN/opGREZ4ugRMI56C/v58FhaBkz58/z00WMtaL1Lp5jhfQB33qCcYFBqKkpIQbHnRveHiYThD0fevWrexGDeOJv5syZQrnTKfp4IRAtl6vN8tJz2eM2skSSc019A5diysqKlg8iTW7Z88engzBOtqzZw97SuF0CU4jNjc388QT5iUYDGYVGes+Rdai5Hyhe2sh1Yhnt7S0MFWMACqRSHADR0D52GOP0d7iTkCkFD7wgQ/Ili1bRCRtkxsbG6mXsMnvvPMOZW13F3UdrGFjh9Mya9Yspl/xfwMDA0xZQq9fe+01visCLei/z+djAS1sTCwWo2x1Ybodl8zmAmx1d3c39Qb6ecMNN3BOIbOf/exnLOa+//77RSS1F7788ssiIuy39atf/UpEUh3WYTfxdWhoiE4WTmkWFhbSmddyHO/eoYkAkZSThnlFOtLhcLBAHc6LDgwgk3nz5tFWYn9EivZ73/se5YRC/VgsxrEgkNadsa2XNb8bTKrLwMDAwMDAYMIg7+JmRAW6CyZQVlZGL3bFihUikjo6ir4Z+P3FixfT40a/F9xmfuDAARY5wTsfGRnJutPJ7/fz/+0oVMtFy4KChUcZjUY5fniz+/btI1OAqPH48eP0wBHZrFmzRkRSdDP+FtH55MmTs9INkUgko3eCHcA4wJrV19czesS4BgcHKSd9dxAiEERdQ0NDLELft2+fiKSjgk996lOcR3QsPXToEGUHytbhcFyzvigYV0dHB98LrGJXVxflg3EvXryY6S9Qz/rGasjs2WefFZEUCwZaHX1VOjo6MvRTJBWN2s1m5SrmR2QM1mDevHnUL8jM6/XynXHsedeuXWQCdAGjSIr50d3TRVJMi/X3EokEGSE7bme3Fv46HA5+PliBVatWyVe/+lUREdmxYwfHgqJ6pNCHhoYowy9/+csikmaD2tvbScdD5iLpdal7qNgN6Aki2sLCwoyWEiIplhHzidvHZ82axblAWuHmm2/OKJAVEfna177G51rvUdJ3ZkE34vG47fYGegLdrKqqYnoc68/tdmcVxn/mM5/h/gEGYeXKlVxnOFSB++ZWrFhB5gPPiEajTBdBtmNjY7bbG4wRLGg0GqUMkAEIBoMsZMbvV1dX88g+3n3u3LlMiaEtjGYakaaGPbv55pvJ0iLtlIv9yGfMuVLYGAuYp1AoxD0QOjk8PMx1iX00Go2SwcRXMEB6naIUxOFwkFXSjJO1V9vVjM8wPgYGBgYGBgYTBnkXN+uoAJEH6h9Onz7NpkwoUL58+TLz8ijUW7NmTcY9MyLpm3m3b99OzxYROGoUrO+DaMiO4+zWZ+j7j+Cll5aWMjpGFFFTU8N7u8D4OJ1OFsPimB9qSnTRNGoJjh49yqgHUYCOnO2KUhANgfFxOByMbvF/ly5dopcND3zWrFlsiIb3jEajjFQwNn2fEiI1RHijo6OsI0J9wejo6DXraqybKoKZ0kXiyFPj/8rKyjgORMaFhYWsGUFkhbqscDhMPcU8lJeXM0LS3Y0x39Z3zHeM+p4gfQO1SEp/sT6x1o4fP841CCbO6/VSR6HnujgSESSi9lAolMFSAHY1ZxTJrB0SSRWsYj1gfezatYu1HriX62Mf+xh1F/P/0ksvUXaISqFzkyZNYqSs2QHMG8aebzF6Lljv4SsoKCD7gkja6/WyFlK37oDswKQ//vjjfGfYTLC2TU1NZMFgu/bu3UubijUeiURslSHeVSTN3Hk8HtbM6Zo0NGREUXkikWDbDKzT/fv3U3fx7qj72rp1awbDKpJaw5CfZibtZl91h3iRlG3FeMH4VFRUkOVGsXYsFmNdDOS5adMmFn1j78E+kkwmmTXAei0qKsoYm0hqzdpZvwRbA33SxcVg3Hp6euTYsWMikma6b7rpJuob5HD8+HFmB6ytM9rb2ylPPGv27NnUFzx3vGOzrXOz0+lkwREUdmRkhA4PNoOenp4MqlEkdQkZLmGD44MNJRKJ0IHABI+NjWUVFdrdcdOKXKccxsbGOC44LRcvXqRS4L17enq4YCF0GNhYLEZjo3uD4Pf0uDDma5UO0tA9J/B+cGhfffVVGicoYCAQ4AaJ34fjcOnSpaxTeD6fj3pg3UyvNfB+uj8MfoZTZ/o0G9IpZWVldILg+GHj7ezsZBEexlNQUECdtfYTuhbAeGKxGDdL6GUkEqEugYafP38+T1/g/To7Ozk2OE14lt/vp4y0YbWe9LJ+bxf0HCJljE1vYGCA1zTAefB4PCxgBmA4NdATJ5FIUHZIeQ4NDdHJsuty4FywFkvH4/GsyxcDgQAvN8YmEwgEuGls2rRJRFIbLOwiNkqkg/bu3ct1CV0cHh6mXK0nDq819MEKfC7mHk4resCJpMf99a9/nWtr8+bNIpI+fBEOh2l7tQNiDaquhQNrnTePx8N30Kc4YVMgn5KSEh4sgVzuvPNOyhabv+5lh+dh7gKBAB12vT/afR2HRiwWy7rMVr8b9sJQKMSien2xOOS0fPnyjOdeunRJ2traRCRdyFxcXJzVq2+8MKkuAwMDAwMDgwmDvIub+SCnk14YogeXy5UR/eL/4MHBsx0dHWVRExgfpEncbjd/T6dhrEe7x8bGbPfeRTIvubSOz+128zMRbej+L2BIurq6WBSKfhq5ClF1tJcr4rrWUVgikchI/4hkFgCik2x5eTkZEn0HGb4HjYvizLGxMUbmubrAXsuIBNBHx62X6Yqk+31gjMlkkvIDy1NUVMQoFAweZFdWVka91vdHgQ2xs9XCv4PuX6X1DN9jjYmkU9A6JYdIy5qacLlclDsiL90T5Fqsv1xwOByM9jH/Pp+PDBXesbu7m5EyIsvS0lLKQHfwFUmxY9ai7JGRkawLUa8HRkdHs9K0TqeTdhFRczwep3z0OtKdwvUzpk+fzmfo7r5gWXRfousByAIyGxkZoY0Aq3fjjTdyjGhF4fV6aUthW/CsqqoqMsu51uL10FMtO6wjsDXd3d08vAL2TSTd9wxM+OXLl7PaxiCb4vF4uE5hb3OVQ1zN0W67AB1LJBLUT8iwoqIi6+i6vm0B9hQ6XF5ezhYomtGyKzVpGB8DAwMDAwODCQNb3cFceTdr1ALvTSTtoc6ZM4eFXYjkdM7X+qxYLJazruBaQjM+uikb2B14rsFgMOtYf3l5OT1V/D5YLK/Xm1WUrRmt6w28CyINl8vFiAIy0bd6Q666m631+Luu/wJcLhfHiHHn2/32auBwOLKOP2pmEjVb+l2QZy8pKeHYEJmgZkTrB/7O5XJlrYnrMUYRyXoXXZ+Dr/39/VltG4qKirIK+7V8oAOQ+/Vafxq6M6uWIRgM2BC3202WWHeah6wReQJut5vP03V8dje3u1pYo3afz8dIGv83NDRE24Ovvb29fH+sU4zB5/Nxjev6F2ttz/WSq9XOORyOjBYpIil7gnFrhh+sFsYBJsvr9easx7KyrVfT4dcOWO8Di8fjlIHObIDNgRz1UW3YHTBeyWQyq2N6IpHIaM4ocn0YZp0dwFfdCV4kZWusv6cLvzE+MH+jo6Ncz9grXS5Xzqav4xnjNeXB9ATwA53OrMJdp9NJoVsHpmlJPbH/CVg3BL249EkFbPL63TEu6/h0ilAL8HobICu0k2ctCgyFQnTggFypxlwpLD1G6xUj1wPJZDJLFiJpXYTjU1BQQGOrnXWrDmCTdblcWcYmmUxmdS6+Hk6Pfk/IQBt5fdksxqFPSeBdrXLRKbT/lF6K5A6G9IlEfNXj08GFNeWB5+k+UvozrlcK719BXwSNcaAgWyQ9NujWlStX+P5wIqAH/y6t/J8eq/58bXdgb3BIIplM8ndRrK/X3/Xc+N8NOrWuYe12nkunx8bGOG78TJdFWNOT/+p51wu57CqAdxWRjD5NOBCTC9agRcS+cZlUl4GBgYGBgcGEQcF7idwKCgouicg71+51rhlmJJPJ7OY/FvwPj0/k/3+MVzU+ETPG/3IYPf0nzBj/q2HG+E/8P47vPTk+BgYGBgYGBgb/yzCpLgMDAwMDA4MJA+P4GBgYGBgYGEwYGMfHwMDAwMDAYMLAOD4GBgYGBgYGEwbG8TEwMDAwMDCYMDCOj4GBgYGBgcGEgXF8DAwMDAwMDCYMjONjYGBgYGBgMGFgHB8DAwMDAwODCYN/AOuLy+1fh8HdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 100 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import Principal Components Analysis module\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "# extract 100 \"eigen-digits\"\n",
    "pca = PCA(n_components=100)\n",
    "pca.fit(images_X)\n",
    "\n",
    "# graph the 100 components\n",
    "plt.figure(figsize=(10, 10))\n",
    "for i, comp in enumerate(pca.components_):\n",
    "    plt.subplot(10, 10, i + 1)\n",
    "    plt.imshow(comp.reshape((28, 28)), cmap=plt.cm.gray_r)\n",
    "    plt.xticks(())\n",
    "    plt.yticks(())\n",
    "plt.suptitle('100 components extracted by PCA')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6374141399357542"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca.explained_variance_ratio_[:30].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a1b678810>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_pca = PCA(n_components=784)\n",
    "full_pca.fit(images_X)\n",
    "\n",
    "plt.plot(np.cumsum(full_pca.explained_variance_ratio_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.61090568,  1.36377972,  0.42170384, -2.19662829, -0.45181076,\n",
       "        -1.32049499,  0.79434674,  0.30551117,  1.22978974, -0.7209673 ,\n",
       "         0.08168339, -1.91375643, -2.54647373, -1.62440679,  0.67107145,\n",
       "         0.1563566 ,  0.91831558, -0.18982437,  1.30140758,  1.57928671,\n",
       "         0.9905427 ,  0.11280097,  1.07342107,  0.70139229, -0.35905429,\n",
       "         0.16656112,  0.99308919, -0.73113379,  0.8696472 , -0.18636832,\n",
       "        -0.72503278,  0.11262073,  0.16117266,  0.07331158,  0.11731471,\n",
       "        -0.72983437, -0.2965799 ,  0.17303952,  0.29895068,  2.32448734,\n",
       "        -0.20362047, -0.85407518,  0.67660044,  0.3479519 ,  0.34089375,\n",
       "        -0.42147508, -0.20665435,  0.3932703 , -0.31692782,  0.38499973,\n",
       "         0.06153345,  0.07791799,  0.62888125,  0.79420447, -0.41382821,\n",
       "         0.03777706, -0.18031172,  0.16394444, -0.51442222, -0.36673658,\n",
       "        -0.40994848, -0.47807315,  0.48378358,  0.29852338,  0.2135774 ,\n",
       "         0.78757919, -0.7147907 ,  0.41096491, -0.223465  , -0.07354244,\n",
       "        -0.14075359,  0.55837601,  0.49854072,  0.60304742,  0.09958459,\n",
       "         0.05654119,  0.73490303, -0.12210787, -0.8162962 ,  0.33544017,\n",
       "        -0.03344693,  0.08870677, -0.00580449,  0.05647073, -0.21902263,\n",
       "        -0.32300042,  0.4535495 , -0.58071342, -0.07016463,  0.29297981,\n",
       "         0.37014839, -0.56460096, -0.17789919, -0.01086679,  0.28705588,\n",
       "         0.28670933, -0.0779205 , -0.32722502, -0.4866675 , -0.19796331]])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use pca to transform the first image\n",
    "pca.transform(images_X[:1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.61090568,  1.36377972,  0.42170384, -2.19662829, -0.45181076,\n",
       "        -1.32049499,  0.79434674,  0.30551117,  1.22978974, -0.7209673 ,\n",
       "         0.08168339, -1.91375643, -2.54647373, -1.62440679,  0.67107145,\n",
       "         0.1563566 ,  0.91831558, -0.18982437,  1.30140758,  1.57928671,\n",
       "         0.9905427 ,  0.11280097,  1.07342107,  0.70139229, -0.35905429,\n",
       "         0.16656112,  0.99308919, -0.73113379,  0.8696472 , -0.18636832,\n",
       "        -0.72503278,  0.11262073,  0.16117266,  0.07331158,  0.11731471,\n",
       "        -0.72983437, -0.2965799 ,  0.17303952,  0.29895068,  2.32448734,\n",
       "        -0.20362047, -0.85407518,  0.67660044,  0.3479519 ,  0.34089375,\n",
       "        -0.42147508, -0.20665435,  0.3932703 , -0.31692782,  0.38499973,\n",
       "         0.06153345,  0.07791799,  0.62888125,  0.79420447, -0.41382821,\n",
       "         0.03777706, -0.18031172,  0.16394444, -0.51442222, -0.36673658,\n",
       "        -0.40994848, -0.47807315,  0.48378358,  0.29852338,  0.2135774 ,\n",
       "         0.78757919, -0.7147907 ,  0.41096491, -0.223465  , -0.07354244,\n",
       "        -0.14075359,  0.55837601,  0.49854072,  0.60304742,  0.09958459,\n",
       "         0.05654119,  0.73490303, -0.12210787, -0.8162962 ,  0.33544017,\n",
       "        -0.03344693,  0.08870677, -0.00580449,  0.05647073, -0.21902263,\n",
       "        -0.32300042,  0.4535495 , -0.58071342, -0.07016463,  0.29297981,\n",
       "         0.37014839, -0.56460096, -0.17789919, -0.01086679,  0.28705588,\n",
       "         0.28670933, -0.0779205 , -0.32722502, -0.4866675 , -0.19796331]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reminder that transformation is a matrix multiplication away\n",
    "np.dot(images_X[:1]-images_X.mean(axis=0), pca.components_.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# instantiate our BernoulliRBM\n",
    "# we set a random_state to initialize our weights and biases to the same starting point\n",
    "# verbose is set to True to see the fitting period\n",
    "# n_iter is the number of back and forth passes\n",
    "# n_components (like PCA and LDA) represent the number of features to create\n",
    "# n_components can be any integer, less than , equal to, or greater than the original number of features\n",
    "rbm = BernoulliRBM(random_state=0, verbose=True, n_iter=20, n_components=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[BernoulliRBM] Iteration 1, pseudo-likelihood = -138.59, time = 0.48s\n",
      "[BernoulliRBM] Iteration 2, pseudo-likelihood = -120.25, time = 0.55s\n",
      "[BernoulliRBM] Iteration 3, pseudo-likelihood = -116.46, time = 0.53s\n",
      "[BernoulliRBM] Iteration 4, pseudo-likelihood = -118.42, time = 0.53s\n",
      "[BernoulliRBM] Iteration 5, pseudo-likelihood = -112.37, time = 0.51s\n",
      "[BernoulliRBM] Iteration 6, pseudo-likelihood = -109.97, time = 0.50s\n",
      "[BernoulliRBM] Iteration 7, pseudo-likelihood = -116.41, time = 0.50s\n",
      "[BernoulliRBM] Iteration 8, pseudo-likelihood = -109.70, time = 0.51s\n",
      "[BernoulliRBM] Iteration 9, pseudo-likelihood = -112.17, time = 0.51s\n",
      "[BernoulliRBM] Iteration 10, pseudo-likelihood = -105.04, time = 0.49s\n",
      "[BernoulliRBM] Iteration 11, pseudo-likelihood = -104.57, time = 0.49s\n",
      "[BernoulliRBM] Iteration 12, pseudo-likelihood = -104.95, time = 0.52s\n",
      "[BernoulliRBM] Iteration 13, pseudo-likelihood = -109.09, time = 0.50s\n",
      "[BernoulliRBM] Iteration 14, pseudo-likelihood = -110.33, time = 0.49s\n",
      "[BernoulliRBM] Iteration 15, pseudo-likelihood = -107.89, time = 0.49s\n",
      "[BernoulliRBM] Iteration 16, pseudo-likelihood = -104.67, time = 0.48s\n",
      "[BernoulliRBM] Iteration 17, pseudo-likelihood = -107.90, time = 0.49s\n",
      "[BernoulliRBM] Iteration 18, pseudo-likelihood = -110.65, time = 0.51s\n",
      "[BernoulliRBM] Iteration 19, pseudo-likelihood = -99.74, time = 0.53s\n",
      "[BernoulliRBM] Iteration 20, pseudo-likelihood = -104.83, time = 0.50s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BernoulliRBM(batch_size=10, learning_rate=0.1, n_components=100, n_iter=20,\n",
       "             random_state=0, verbose=True)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rbm.fit(images_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# RBM also has components_ attribute\n",
    "len(rbm.components_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 100 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the RBM components (representations of the new feature sets)\n",
    "plt.figure(figsize=(10, 10))\n",
    "for i, comp in enumerate(rbm.components_):\n",
    "    plt.subplot(10, 10, i + 1)\n",
    "    plt.imshow(comp.reshape((28, 28)), cmap=plt.cm.gray_r)\n",
    "    plt.xticks(())\n",
    "    plt.yticks(())\n",
    "plt.suptitle('100 components extracted by RBM')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100,)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(rbm.components_.mean(axis=1)).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.57210581e-16, 3.12674619e-15, 6.56801258e-09, 1.17553521e-02,\n",
       "       3.55578293e-18, 7.02915447e-14, 4.21962691e-10, 1.54217465e-10,\n",
       "       1.76321641e-21, 5.85395668e-07, 3.17026495e-05, 2.51711525e-03,\n",
       "       2.56169958e-22, 5.78541642e-14, 1.00000000e+00, 4.87877940e-03,\n",
       "       1.05786939e-13, 1.39142955e-06, 4.87960846e-01, 2.76978069e-09,\n",
       "       3.39250487e-15, 9.97238624e-01, 3.68202289e-11, 2.35118749e-06,\n",
       "       7.70435192e-14, 1.03613438e-17, 1.56407217e-04, 6.73556712e-05,\n",
       "       9.85353155e-01, 1.00000000e+00, 2.81115665e-05, 2.15653464e-05,\n",
       "       8.79972795e-17, 3.25746311e-10, 9.99999997e-01, 1.13384170e-17,\n",
       "       2.28772018e-14, 1.69237377e-14, 2.86813102e-05, 7.68772482e-11,\n",
       "       8.11884149e-17, 9.99997736e-01, 1.31865941e-13, 1.03354360e-11,\n",
       "       2.56073911e-07, 9.99413987e-01, 1.02664878e-11, 2.02808258e-16,\n",
       "       3.11422462e-07, 1.00000000e+00, 5.48466520e-26, 1.07004015e-20,\n",
       "       5.45991767e-16, 5.83877447e-13, 4.92741842e-18, 2.64365375e-12,\n",
       "       1.00000000e+00, 1.26255495e-07, 9.99949532e-01, 3.11600450e-09,\n",
       "       1.19406740e-06, 2.61359471e-06, 1.00000000e+00, 1.00000000e+00,\n",
       "       1.02029859e-04, 1.11007522e-09, 3.31889393e-08, 3.65888342e-09,\n",
       "       1.02432641e-12, 1.00000000e+00, 3.42260219e-14, 2.35496946e-19,\n",
       "       4.48364149e-19, 1.64199456e-13, 9.26823003e-13, 3.98698387e-16,\n",
       "       7.24389543e-16, 7.08635101e-04, 1.42652350e-06, 2.50925842e-06,\n",
       "       1.62361239e-10, 4.04013623e-17, 9.99998612e-01, 9.99989692e-01,\n",
       "       4.99602390e-25, 5.25594461e-12, 1.58074301e-14, 2.26035777e-14,\n",
       "       1.84236442e-31, 5.39184171e-16, 1.65450607e-16, 3.52988322e-19,\n",
       "       9.99998512e-01, 1.47898097e-09, 1.16733466e-03, 9.78396275e-08,\n",
       "       1.69348862e-14, 2.03367031e-20, 1.85772496e-17, 6.15140217e-16])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_new_features = rbm.transform(images_X[:1]).reshape(100,)\n",
    "\n",
    "image_new_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ -2.73812671, -10.71022413,  -9.32197824,  13.17500053,\n",
       "         -8.90236709,  -0.65738837,   0.96176768, -29.92032627,\n",
       "        -28.2409098 ,  -2.43939535,   7.76034755,  19.04085926,\n",
       "        -24.38256336,  -7.56701072,   7.29931339,   7.52074384,\n",
       "          0.49223382,  -0.35822841,  13.98858891,  -0.16378608,\n",
       "        -12.99876115,  24.67771066, -15.98991919,   5.55894757,\n",
       "          0.7503061 ,  -4.97790527,   2.52460981,  13.29094074,\n",
       "         21.03538981,  17.12198593,   2.35030272,   5.26868007,\n",
       "        -25.80548456,   4.87102279,  35.18765648, -17.33167717,\n",
       "        -12.75020031,  14.55022915,  -2.15243992, -44.35997282,\n",
       "        -20.18627545,  27.05490996,  -9.59166933, -15.37317282,\n",
       "         -5.43789982,  18.38155093,  -6.36146665, -18.33808988,\n",
       "         -9.50893763,  33.20146018, -27.73274878, -20.79994691,\n",
       "         -7.58492586,  -9.11001031, -17.17581532,   1.64841259,\n",
       "         24.63633079,  -5.00170621,   9.06808124,   1.83606506,\n",
       "         -1.5544963 ,   4.2489287 ,   7.00819526,   7.14856163,\n",
       "         16.3215343 , -12.05604522,   9.37535744,  -6.73869856,\n",
       "          0.30883906,   7.1171987 ,   5.7372381 , -18.19781641,\n",
       "        -19.05312399,  -7.82225821,  -0.95339744,  -7.13851422,\n",
       "        -21.52604831,   8.57574553,   0.30854817,   3.69937354,\n",
       "         -2.13719439,  -3.94511148,  13.81696416,  19.97568067,\n",
       "        -25.7988699 ,  -6.29729114,  -2.26639765,   0.67607951,\n",
       "        -39.70561527,  -3.44343166,  -2.21132994, -21.85929703,\n",
       "         37.72000075, -17.22028501,  10.00443004,  11.84621742,\n",
       "         -3.46455658, -15.27152789, -13.77762037,  -8.32958909]])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.dot(images_X[:1]-images_X.mean(axis=0), rbm.components_.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[62 69 14 56 63 29 49 34 82 92 41 83 58 45 21 28 18  3 15 11]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([1.        , 1.        , 1.        , 1.        , 1.        ,\n",
       "       1.        , 1.        , 1.        , 0.99999861, 0.99999851,\n",
       "       0.99999774, 0.99998969, 0.99994953, 0.99941399, 0.99723862,\n",
       "       0.98535315, 0.48796085, 0.01175535, 0.00487878, 0.00251712])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_features = image_new_features.argsort()[-20:][::-1]\n",
    "\n",
    "print(top_features)\n",
    "image_new_features[top_features]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x1800 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(25, 25))\n",
    "for i, comp in enumerate(top_features):\n",
    "    plt.subplot(5, 4, i + 1)\n",
    "    plt.imshow(rbm.components_[comp].reshape((28, 28)), cmap=plt.cm.gray_r)\n",
    "    plt.title(\"Component {}, feature value: {}\".format(comp, round(image_new_features[comp], 2)), fontsize=20)\n",
    "plt.suptitle('Top 20 components extracted by RBM for first digit', fontsize=30)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x1800 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bottom_features = image_new_features.argsort()[:20]\n",
    "\n",
    "plt.figure(figsize=(25, 25))\n",
    "for i, comp in enumerate(bottom_features):\n",
    "    plt.subplot(5, 4, i + 1)\n",
    "    plt.imshow(rbm.components_[comp].reshape((28, 28)), cmap=plt.cm.gray_r)\n",
    "    plt.title(\"Component {}, feature value: {}\".format(comp, round(image_new_features[comp], 2)), fontsize=20)\n",
    "plt.suptitle('Bottom 20 components extracted by RBM for first digit', fontsize=30)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_split.py:1978: FutureWarning: The default value of cv will change from 3 to 5 in version 0.22. Specify it explicitly to silence this warning.\n",
      "  warnings.warn(CV_WARNING, FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "({'C': 0.1}, 0.8908333333333334)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "# create our logistic regression\n",
    "lr = LogisticRegression()\n",
    "params = {'C':[1e-2, 1e-1, 1e0, 1e1, 1e2]}\n",
    "\n",
    "# instantiate a gridsearh class\n",
    "grid = GridSearchCV(lr, params)\n",
    "\n",
    "# fit to our data\n",
    "grid.fit(images_X, images_y)\n",
    "\n",
    "# check the best params\n",
    "grid.best_params_, grid.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_split.py:1978: FutureWarning: The default value of cv will change from 3 to 5 in version 0.22. Specify it explicitly to silence this warning.\n",
      "  warnings.warn(CV_WARNING, FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "({'clf__C': 1.0, 'pca__n_components': 100}, 0.8878333333333334)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = LogisticRegression()\n",
    "pca = PCA()\n",
    "\n",
    "params = {'clf__C':[1e-1, 1e0, 1e1],\n",
    "         'pca__n_components': [10, 100, 200]}\n",
    "\n",
    "# create our pipeline\n",
    "pipeline = Pipeline([('pca', pca), ('clf', lr)])\n",
    "\n",
    "# instantiate a gridsearh class\n",
    "grid = GridSearchCV(pipeline, params)\n",
    "\n",
    "# fit to our data\n",
    "grid.fit(images_X, images_y)\n",
    "\n",
    "# check the best params\n",
    "grid.best_params_, grid.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_split.py:1978: FutureWarning: The default value of cv will change from 3 to 5 in version 0.22. Specify it explicitly to silence this warning.\n",
      "  warnings.warn(CV_WARNING, FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "/Users/super/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "({'clf__C': 1.0, 'rbm__n_components': 200}, 0.9178333333333333)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rbm = BernoulliRBM(random_state=0)\n",
    "\n",
    "params = {'clf__C':[1e-1, 1e0, 1e1],\n",
    "          'rbm__n_components': [100, 200]\n",
    "         }\n",
    "\n",
    "# create our pipeline\n",
    "pipeline = Pipeline([('rbm', rbm), ('clf', lr)])\n",
    "\n",
    "# instantiate a gridsearh class\n",
    "grid = GridSearchCV(pipeline, params)\n",
    "\n",
    "# fit to our data\n",
    "grid.fit(images_X, images_y)\n",
    "\n",
    "# check the best params\n",
    "grid.best_params_, grid.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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